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Pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer patients is related to a favorable prognosis. The identification of early biomarkers predictive of pathological complete response would help optimize the multimodality management of the patients. A panel of 11 tumor-related proteins was investigated by immunohistochemistry in the pretreatment biopsy of a group of locally advanced rectal cancer patients to identify early biomarkers of pathological complete response to neoadjuvant chemoradiotherapy. A mono-institutional retrospective cohort of 95 stage II/III locally advanced rectal cancer patients treated with neoadjuvant chemoradiotherapy and surgery was selected based on clinicalpathological characteristics and the availability of a pretreatment tumor biopsy. Eleven selected protein marker expression (MLH1, GLUT1, Ki67, CA-IX, CXCR4, COX2, CXCL12, HIF1, VEGF, CD44, and RAD51) was investigated. The optimal cutoff values were calculated by receiver operating characteristic curve analysis. Classification and regression tree analysis was performed to investigate the biomarker interaction. Patients presenting either Ki-67 or HIF1 or RAD51 below the cutoff value, or CXCR4 or COX2 above the cutoff value, were more likely to get a pathological complete response. Classification and regression tree analysis identified three groups of patients resulting from the combination of Ki-67 and CXCR4 expression. Patients with high expression of Ki-67 had the lowest chance to get a pathological complete response (18%), as compared to patients with low expression of both Ki-67 and CXCR4 (29%), and patients with low Ki-67 and high CXCR4 expression (70%). Pretreatment Ki-67, CXCR4, COX2, HIF1, and RAD51 in tumor biopsies are associated with pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer. A combined evaluation of Ki-67 and CXCR4 would increase their predictive potential. If validated, their optimal cutoff could be used to select patients for a tailored multimodality treatment.

Take Home Message Four promising biomarkers were found to be predictive for intravesical mitomycin C in non–muscle-invasive bladder cancer patients. Prospective validation is needed., Background Currently, no biomarkers of response to mitomycin C have been identified in non–muscle-invasive bladder cancer patients. Predictive biomarkers could improve the treatment outcome and eliminate adverse events from unnecessary treatment. Objective To identify and validate predictive biomarkers of chemoresection with mitomycin C. Design, setting, and participants The intervention group of a randomised controlled trial was identified for analyses. The study was conducted between January 2018 and June 2019 in two major urological departments in Denmark. Patients had a history of Ta low-grade/high-grade disease and were included upon recurrence. The intervention group (58 patients) received chemoresection with mitomycin C. Tumour and reference germline DNA from prior tumours were analysed by whole exome sequencing. Predictive biomarkers were validated in the context of Ta low-grade tumours from the UROMOL study. Outcome measurements and statistical analysis Response to chemotherapy (intervention group from the randomised controlled trial) and recurrence-free survival (UROMOL cohort) were measured. Groups were compared using Fisher’s exact test and Wilcoxon rank sum test. Results and limitations Chemoresponse was associated with the mutation status of SPTAN1, APC, and FGFR3, and the level of APOBEC signature contribution (p = 0.035, p = 0.034, p = 0.055, and p = 0.035, respectively). The main limitations include no biopsy for biomarker discovery immediately prior to chemoresection and the unmatched validation cohort. Conclusions Mutation status of APC, SPTAN1, and FGFR3 and the level of mutational contribution from APOBEC-related signatures were identified as potential predictive biomarkers for chemoresection with mitomycin C in non–muscle-invasive bladder cancer patients. A prospective validation study is however needed. Patient summary We investigated DNA from noninvasive bladder tumours in order to predict treatment response to chemotherapy. Four biomarkers showed promising results, which should be tested in future studies.

A decade ago, immune checkpoint blockade emerged as a major breakthrough in oncology, proposing a novel approach by which immune brakes could be released to enhance antitumor responses. Despite apparently modest improvement of the median duration of response, a spectacular doubling of long-term responses as compared to the available standard of care was seen, for instance, in metastatic melanoma. It soon became obvious that the percentage of patients responding to these novel approaches is relatively small, and the importance of an accurate prediction of responders became more and more clear. Strong predictive markers would allow for the administration of immune checkpoint blocker therapy to the patients most likely to benefit from it, and sparing the potential non-responders of a treatment which is far from innocuous, being associated with significant side-effects and, not least, an important price tag. A number of potential response predictors have already been investigated and partly validated, but they do not cover the major unmet need encountered in the current clinical setting. Here, we review biomarkers for immune checkpoint blockade efficacy, either clinically validated and currently in use, or which have been proposed as candidates and are currently under investigation.

Purpose of the review The neuromuscular complications of cancer therapy include chemotherapy-induced peripheral neurotoxicity (CIPN), immune-related neuromuscular complications to immune checkpoint inhibitors and radiation-induced neuropathy/plexopathy. With a wider focus on CIPN, we will discuss new pathogenetic insights, recent predictive biomarkers and emerging therapies for neuromuscular complications of cancer therapy. Recent findings Findings from recent preclinical studies have improved our knowledge on new CIPN pathogenetic pathways, including the activation of senescence-like processes in neurons, axonal degeneration and neuroinflammation. Metabolomics and serum neurofilament light chain levels appear the most promising biomarkers to predict CIPN development and severity. There is some recent evidence of promising pharmacological compounds to prevent or treat CIPN, and new drugs are in early development and testing. Summary A multimodal assessment, with neurophysiological, imaging and patient-reported outcome measures, coupled with the use of reliable blood or genetic biomarkers, may offer pathogenetic grounds for future preventive and symptomatic strategies for the multidisciplinary treatment of neuromuscular complications of cancer therapy.

Immunotherapy in the form of ICIs has revolutionized advanced NSCLC treatment algorithms, with ICI-containing combination treatments being the latest addition to approved regimens. However, PD-L1 still represents the only routinely assessed and validated biomarker apart from genetic drivers testing, impairing our capacity to personalize and guide treatment. Therefore, this paper aims to analyze the most promising emerging predictive biomarkers that could help us in the near future to select patients more effectively.

Yuanguo Luo,1,* Bo Lv,2,3,* Shaokang He,4,* Kai Zou,1 Kezhi Hu2,3 1Department of Orthopedics, The 923rd Hospital of the Joint Logistics Support Force of the People’s Liberation Army, Nanning, People’s Republic of China; 2Department of Orthopedics, People’s Hospital of Guilin, Guilin, Guangxi, 541001, People’s Republic of China; 3Department of Orthopedics, Fifth Clinical Medical College, Guilin Medical University, Guilin, Guangxi, 541001, People’s Republic of China; 4Department of Orthopedics, The Tenth People’s Hospital of Nanning, Nanning, Guangxi, 530105, People’s Republic of China*These authors contributed equally to this workCorrespondence: Bo LvPeople’s Hospital of Guilin, 12 Wenming Road, Guilin, Guangxi, 541001, People’s Republic of ChinaTel +867738997962Email bolv198012@163.comPurpose: Osteosarcoma is the most common malignant bone cancer affecting adolescents and young adults. This study aimed to screen potential diagnostic and therapeutic markers for osteosarcoma.Methods: Differential expression analysis between osteosarcoma and control was performed in GSE99671, the differentially expressed genes (DEGs) were subjected to co-expression analysis. Enrichment analysis was employed to identify the biological functions and KEGG signaling pathways of module genes. In addition, a differential analysis was also performed between recurrent and non-recurrent osteosarcoma samples in GSE39055, and enrichment analysis was performed for DEGs. Further, Kaplan–Meier curve analysis was performed on the module genes, and receiver operating characteristic (ROC) curve was drawn. Comparison of the module with the highest correlation to osteosarcoma identified key genes. Cox regression model was utilized to identify the predictive ability of key genes for the prognosis of osteosarcoma.Results: A total of 13 co-expression modules were identified from 4871 DEGs of GSE99671, module 1 had the highest positive correlation with osteosarcoma. Module genes were mainly enriched in autophagy and macrophage migration functions. A total of 1126 DEGs were obtained from GSE39055, significantly involved in neutrophil mediated immunity. Screening of genes with area under the ROC curve (AUC) values greater than 0.73 in both GSE99671 and GSE39055 identified 5 key genes when compared with genes from module 1. The nomogram results showed that ATF5, CHCHD8, ENOPH1, and LOC286367 might predict 5-year or 8-year survival time of osteosarcoma patients. The Cox model results confirmed that the signals of ATF5, CHCHD8, and LOC286367 were robust, and it may be used in the diagnosis, treatment, and prognosis of osteosarcoma.Conclusion: We found that ATF5, CHCHD8, and LOC286367 can effectively identify osteosarcoma tumorigenesis and even recurrence status. This is helpful for early diagnosis and treatment, improving the clinical treatment of patients with osteosarcoma.Keywords: osteosarcoma, predictive biomarkers, recurrence, weighted co-expressed network analysis

In personalized medicine, predictive biomarker testing is the basis for an appropriate choice of therapy for patients with cancer. An important tool for laboratories to ensure accurate results is participation in external quality assurance (EQA) programs. Several providers offer predictive EQA programs for different cancer types, test methods, and sample types. In 2013, a guideline was published on the requirements for organizing high-quality EQA programs in molecular pathology. Now, after six years, steps were taken to further harmonize these EQA programs as an initiative by IQNPath ABSL, an umbrella organization founded by various EQA providers. This revision is based on current knowledge, adds recommendations for programs developed for predictive biomarkers by in situ methodologies (immunohistochemistry and in situ hybridization), and emphasized transparency and an evidence-based approach. In addition, this updated version also has the aim to give an overview of current practices from various EQA providers. Electronic supplementary material The online version of this article (10.1007/s00428-020-02928-z) contains supplementary material, which is available to authorized users.

Biliary tract cancer (BTC) is an uncommon and aggressive neoplasm, with most patients presenting in an advanced stage. Systemic chemotherapy is the limited treatment available but is unsatisfactory, while targeted therapy is still awaiting validation from clinical trials. Given the potential effect of immune checkpoint inhibitors (ICIs) in the treatment of BTC, this review aims to summarize the evidence-based benefits and predictive biomarkers for using inhibitors of cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) ligand, or programmed cell death protein-1 and its ligand (PD-1 and PD-L1) as monotherapy or combined with other anti-tumor therapies, while also pointing out certain pitfalls with the use of ICIs which need to be addressed.

Background In the presence of heterogeneous treatment effects, it is desirable to divide patients into subgroups based on their expected response to treatment. This is formalised via a personalised treatment recommendation: an algorithm that uses biomarker measurements to select treatments. It could be that multiple, rather than single, biomarkers better predict these subgroups. However, finding the optimal combination of multiple biomarkers can be a difficult prediction problem. Methods We described three parametric methods for finding the optimal combination of biomarkers in a personalised treatment recommendation, using randomised trial data: a regression approach that models outcome using treatment by biomarker interactions; an approach proposed by Kraemer that forms a combined measure from individual biomarker weights, calculated on all treated and control pairs; and a novel modification of Kraemer’s approach that utilises a prognostic score to sample matched treated and control subjects. Using Monte Carlo simulations under multiple data-generating models, we compare these approaches and draw conclusions based on a measure of improvement under a personalised treatment recommendation compared to a standard treatment. The three methods are applied to data from a randomised trial of home-delivered pragmatic rehabilitation versus treatment as usual for patients with chronic fatigue syndrome (the FINE trial). Prior analysis of this data indicated some treatment effect heterogeneity from multiple, correlated biomarkers. Results The regression approach outperformed Kraemer’s approach across all data-generating scenarios. The modification of Kraemer’s approach leads to improved treatment recommendations, except in the case where there was a strong unobserved prognostic biomarker. In the FINE example, the regression method indicated a weak improvement under its personalised treatment recommendation algorithm. Conclusions The method proposed by Kraemer does not perform better than a regression approach for combining multiple biomarkers. All methods are sensitive to misspecification of the parametric models.

Oesophageal cancer is a devastating disease with poor outcomes and is the sixth leading cause of cancer death worldwide. In the setting of resectable disease, there is clear evidence that neoadjuvant chemotherapy and chemoradiotherapy result in improved survival. Disappointingly, only 15%–30% of patients obtain a histopathological response to neoadjuvant therapy, often at the expense of significant toxicity. There are no predictive biomarkers in routine clinical use in this setting and the ability to stratify patients for treatment could dramatically improve outcomes. In this review, we aim to outline current progress in evaluating predictive transcriptomic biomarkers for neoadjuvant therapy in oesophageal cancer and discuss the challenges facing biomarker development in this setting. We place these issues in the wider context of recommendations for biomarker development and reporting. The majority of studies focus on messenger RNA (mRNA) and microRNA (miRNA) biomarkers. These studies report a range of different genes involved in a wide variety of pathways and biological processes, and this is explained to a large extent by the different platforms and analysis methods used. Many studies are also vastly underpowered so are not suitable for identifying a candidate biomarker. Multiple molecular subtypes of oesophageal cancer have been proposed, although little is known about how these relate to clinical outcomes. We anticipate that the accumulating wealth of genomic and transcriptomic data and clinical trial collaborations in the coming years will provide unique opportunities to stratify patients in this poor-prognosis disease and recommend that future biomarker development incorporates well-designed retrospective and prospective analyses.

Introduction: Here we describe the development of a protein immunofluorescent assay for the detection of nuclear-localized androgen receptor variant 7 (AR-V7) protein within circulating tumor cells (CTCs) identified in patient blood samples. Used in the clinic, the test result serves as a validated biomarker of futility for patients with progressing metastatic castration-resistant prostate cancer (mCRPC) who are treated with androgen receptor targeted therapies (AATT) in whom nuclear-localized AR-V7 CTCs are identified and have received level 2A evidence in the 2019 National Cancer Center Network (NCCN) guidelines (v1.0). Methods: Assay development was completed on the Epic Sciences rare cell detection platform using control cell lines of known AR-V7 status and clinical testing of mCRPC patient samples obtained at the decision point in management. Results and conclusions: Using these samples, all assay parameters, scoring criteria, and clinical cutoffs for positivity were prospectively selected and locked. After assay lock, blinded clinical validation testing was initiated on multiple, independent, clinical cohorts as reported by Scher et al (JAMA Oncol. 2016;2:1441-1449; JAMA Oncol. 2018;4:1179-1186) and Armstrong et al (J Clin Oncol. 2019;37:1120-1129).

Significance Immune checkpoint blockade (ICB) has revolutionized treatment of many cancer types, but the majority of treated patients still do not respond to ICB. There is an urgent need to identify predictive biomarkers of response prior to or shortly after therapy initiation, as well as the underlying mechanisms. Here we utilize a model of bilateral tumor implantations followed by resection and immunotherapy-response assessment to study the tumor microenvironment shortly following treatment, identifying biomarkers for response or resistance at early time points. Our biomarker gene signatures derived from CD8+ T cells significantly segregate patients by survival and associate with patient response to ICB. Our findings provide a general approach for studying mechanisms of resistance to ICB and discovering predictive biomarkers of response., Immune checkpoint blockade (ICB) is efficacious in many diverse cancer types, but not all patients respond. It is important to understand the mechanisms driving resistance to these treatments and to identify predictive biomarkers of response to provide best treatment options for all patients. Here we introduce a resection and response-assessment approach for studying the tumor microenvironment before or shortly after treatment initiation to identify predictive biomarkers differentiating responders from nonresponders. Our approach builds on a bilateral tumor implantation technique in a murine metastatic breast cancer model (E0771) coupled with anti-PD-1 therapy. Using our model, we show that tumors from mice responding to ICB therapy had significantly higher CD8+ T cells and fewer Gr1+CD11b+ myeloid-derived suppressor cells (MDSCs) at early time points following therapy initiation. RNA sequencing on the intratumoral CD8+ T cells identified the presence of T cell exhaustion pathways in nonresponding tumors and T cell activation in responding tumors. Strikingly, we showed that our derived response and resistance signatures significantly segregate patients by survival and associate with patient response to ICB. Furthermore, we identified decreased expression of CXCR3 in nonresponding mice and showed that tumors grown in Cxcr3−/− mice had an elevated resistance rate to anti-PD-1 treatment. Our findings suggest that the resection and response tumor model can be used to identify response and resistance biomarkers to ICB therapy and guide the use of combination therapy to further boost the antitumor efficacy of ICB.

Defects in DNA repair machinery play a critical role in the pathogenesis and progression of human cancer. When they occur, the tumor cells activate error-prone mechanisms which lead to genomic instability and high mutation rate. These defects represent, therefore, a cancer Achilles'heel which could be therapeutically exploited by the use of DNA damage response inhibitors. Moreover, experimental and clinical evidence indicates that DNA repair deregulation has a pivotal role also in promoting immune recognition and immune destruction of cancer cells. Indeed, immune checkpoint inhibitors have received regulatory approval in tumors characterized by high genomic instability, such as melanomas and lung cancer. Here, we discuss how deregulation of DNA repair, through activation of error-prone mechanisms, increases immune activation against cancer. Finally, we address the potential strategies to use DNA repair components as biomarkers and/or therapeutic targets to empower immune-oncology treatment of human cancer.

The benefit of adjuvant chemotherapy in the early stages of colorectal cancer (CRC) is still disappointing and the prediction of treatment outcome quite difficult. Recently, through a transcriptomic approach, we evidenced a role of PNN and KCNQ1OT1 gene expression in predicting response to fluoropyrimidine-based adjuvant chemotherapy in stage III CRC patients. Thus, the aim of this study was to validate in an independent cohort of stages IIIII CRC patients our previous findings. PNN and KCNQ1OT1 mRNA expression levels were evaluated in 74 formalin-fixed paraffin-embedded tumor and matched normal mucosa samples obtained by stages IIIII CRC patients treated with fluoropyrimidine-based adjuvant chemotherapy. PININ, the protein encoded by PNN, was immunohistochemically evaluated in 15 tumor and corresponding normal mucosa samples, selected on the basis of a low, medium, or high mRNA expression tumor/mucosa ratio. PNN and KCNQ1OT1 mRNA mean expression levels were significantly higher in tumor compared with normal tissues. Patients with high PNN or KCNQ1OT1 tumor mRNA levels according to ROC-based cutoffs showed a shorter disease-free survival (DFS) compared with patients with low tumor mRNA gene expression. Also, patients with tumor mRNA expression values of both genes below the identified cutoffs had a significantly longer DFS compared with patients with the expression of one or both genes above the cutoffs. In a representative large cohort of stages IIIII CRC untreated patients retrieved from GEO datasets, no difference in DFS was observed between patients with high and low PNN or KCNQ1OT1 gene expression levels. These data confirm our previous findings and underscore the relevance of PNN and KCNQ1OT1 expression in predicting DFS in early stages of CRC treated with fluoropyrimidine-based adjuvant chemotherapy. If further validated in a prospective case series, both biomarkers could be used to identify patients who benefit from this treatment and to offer alternative chemotherapy regimens to potential unresponsive patients. In relation to the suggested biological role of PNN and KCNQ1OT1 in CRC, they might also be exploited as potential therapeutic targets.

Background and Purpose: Patients with type 2 diabetes (T2D) have increased risk of cardiovascular disease (CVD), encompassing myocardial infarction, stroke, and peripheral vascular disease. We hypothesized that those biomarkers indicative of acute ischemic stroke (AIS) seen in large vessel occlusion (LVO) may also be elevated in T2D and further enhanced by stress conditions; therefore, these proteins represent potentially predictive biomarkers for those T2D patients at high risk of AIS.Methods: We performed an exploratory proteomic analysis in control subjects (n = 23) versus those with type 2 diabetes (T2D) (n = 23) who underwent a hyperinsulinemic clamp study to transient severe hypoglycemia [blood glucose Results: At baseline (BL), PPBP (p < 0.05), THBS1 (p < 0.05), and CDH1 (p < 0.01) were elevated in T2D; LYVE1 was not different between controls and T2D subjects at BL or at subsequent timepoints. PPBP and THBS1 tended to increase at hypoglycemia in both cohorts, though reached significance only in controls (p < 0.05), returning to BL levels post-hypoglycemia. CDH1 levels were higher in T2D at BL, at hypoglycemia and up to 2-h posthypoglycemia, thereafter reverting to BL levels.Conclusion: Elevated levels of PPBP, THBS1, and CDH1, circulatory proteins suggested as biomarkers of AIS due to LVO, may, in T2D patients, be prognostically indicative of a cohort of T2D patients at increased risk of ischaemic stroke. Prospective studies are needed to determine if this reflects future clinical risk.Clinical trial reg. no: NCT03102801.

Abstract Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. This can be achieved by leveraging omics information for accurate molecular characterization of tumors. Tumor tissue biopsies are currently the main source of information for molecular profiling. However, biopsies are invasive and limited in resolving spatiotemporal heterogeneity in tumor tissues. Alternative non-invasive liquid biopsies can exploit patient’s body fluids to access multiple layers of tumor-specific biological information (genomes, epigenomes, transcriptomes, proteomes, metabolomes, circulating tumor cells, and exosomes). Analysis and integration of these large and diverse datasets using statistical and machine learning approaches can yield important insights into tumor biology and lead to discovery of new diagnostic, predictive, and prognostic biomarkers. Translation of these new diagnostic tools into standard clinical practice could transform oncology, as demonstrated by a number of liquid biopsy assays already entering clinical use. In this review, we highlight successes and challenges facing the rapidly evolving field of cancer biomarker research. Lay Summary Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. The discovery of biomarkers for precision oncology has been accelerated by high-throughput experimental and computational methods, which can inform fine-grained characterization of tumors for clinical decision-making. Moreover, advances in the liquid biopsy field allow non-invasive sampling of patient’s body fluids with the aim of analyzing circulating biomarkers, obviating the need for invasive tumor tissue biopsies. In this review, we highlight successes and challenges facing the rapidly evolving field of liquid biopsy cancer biomarker research.

In previous studies on localized GISTs, KIT exon 11 deletions and mutations involving codons 557/558 showed an adverse prognostic influence on recurrence-free survival. In the metastatic setting, there are limited data on how mutation type and codon location might contribute to progression-free survival (PFS) variability to first-line imatinib treatment. We analyzed the type and gene location of KIT and PDGFRA mutations for 206 patients from a GIST System database prospectively collected at an Italian reference center between January 2005 and September 2020. By describing the mutational landscape, we focused on clinicopathological characteristics according to the critical mutations and investigated the predictive role of type and gene location of the KIT exon 11 mutations in metastatic patients treated with first-line imatinib. Our data showed a predictive impact of KIT exon 11 pathogenic variant on PFS to imatinib treatment: patients with deletion or insertion/deletion (delins) in 557/558 codons had a shorter PFS (median PFS: 24 months) compared to the patients with a deletion in other codons, or duplication/insertion/SNV (median PFS: 43 and 49 months, respectively) (p &lt, 0.001). These results reached an independent value in the multivariate model, which showed that the absence of exon 11 deletions or delins 557/558, the female gender, primitive tumor diameter (≤5 cm) and polymorphonuclear leucocytosis (&gt, 7.5 109/L) were significant prognostic factors for longer PFS. Analysis of the predictive role of PDGFRA PVs showed no significant results. Our results also confirm the aggressive biology of 557/558 deletions/delins in the metastatic setting and allow for prediction at the baseline which GIST patients would develop resistance to first-line imatinib treatment earlier.

Simple Summary Prostate cancer research has been recently characterized by the discovery of several prognostic and predictive molecular factors, which ultimately improve patients’ management. In this review, we present the clinical impact of such factors and the methods to detect them, both on tissue and blood, in advanced prostate cancer patients. The aim of this review is ultimately to depict the role of these molecular factors in the era of precision oncology. Abstract Prostate cancer (PCa) therapy has been recently revolutionized by the approval of new therapeutic agents in the metastatic setting. However, the optimal therapeutic strategy in such patients should be individualized in the light of prognostic and predictive molecular factors, which have been recently studied: androgen receptor (AR) alterations, PTEN-PI3K-AKT pathway deregulation, homologous recombination deficiency (HRD), mismatch repair deficiency (MMRd), and tumor microenvironment (TME) modifications. In this review, we highlighted the clinical impact of prognostic and predictive molecular factors in PCa patients’ outcomes, identifying biologically distinct subtypes. We further analyzed the relevant methods to detect these factors, both on tissue, i.e., immunohistochemistry (IHC) and molecular tests, and blood, i.e., analysis of circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA). Moreover, we discussed the main pros and cons of such techniques, depicting their present and future roles in PCa management, throughout the precision medicine era.

Calorie restriction during gestation in rats has long-lasting adverse effects in the offspring. It induces metabolic syndrome-related alterations, which are partially reversed by leptin supplementation during lactation. We employed these conditions to identify transcript-based nutrient sensitive biomarkers in peripheral blood mononuclear cells (PBMCs) predictive of later adverse metabolic health. The best candidate was validated in humans. Transcriptome analysis of PBMCs from adult male Wistar rats of three experimental groups was performed: offspring of control dams (CON), and offspring of 20% calorie-restricted dams during gestation without (CR) and with leptin supplementation throughout lactation (CR-LEP). The expression of 401 genes was affected by gestational calorie restriction and reversed by leptin. The changes preceded metabolic syndrome-related phenotypic alterations. Of these genes, Npc1 mRNA levels were lower in CR vs CON, and normalized to CON in CR-LEP. In humans, NPC1 mRNA levels in peripheral blood cells (PBCs) were decreased in subjects with mildly impaired metabolic health compared to healthy subjects. Therefore, a set of potential transcript-based biomarkers indicative of a predisposition to metabolic syndrome-related alterations were identified, including NPC1, which was validated in humans. Low NPC1 transcript levels in PBCs are a candidate biomarker of increased risk for impaired metabolic health in humans.

Paper description: Papillary thyroid carcinoma (PTC), usually curable, sometimes progresses to aggressive forms. Analysis of molecular alterations is helpful in predicting disease course and therapy decisions. BRAF gene mutations and epidermal growth factor receptor (EGFR) overexpression are associated with advanced stages of malignancy in several human cancers. We report that in PTC, when present as a single alteration, BRAFV600E mutation or EGFR overexpression both correlate with adverse clinical parameters and their simultaneous presence significantly enhances the frequency of lymph metastases and local tumor invasion. The coexistence of BRAFV600E mutation and EGFR overexpression identifies high risk patients as candidates for more serious treatment. Abstract: Papillary thyroid carcinoma (PTC) generally has a good prognosis, but in a subset of patients it progresses to aggressive forms. Analysis of molecular alterations in relation to clinical phenotype may help in risk stratification of patients by predicting tumor aggressiveness. We analyzed the expression profiles of epidermal growth factor receptor (EGFR) using immunohistochemistry and the presence of BRAF(V600E) mutation by mutant allele-specific PCR in PTC tissue samples (n=92) in relation to clinicopathological parameters. BRAFV600E was detected in 46.7% of patients and correlated with the presence of lymph node metastasis (LNM, p=0.035) and extrathyroid invasion (EI, p

Different mutational burden only partially explains the different response of MSI and MSS CRCs to immunotherapy. Neoantigen load, as measured using available prediction algorithms, is not sufficiently accurate for implementation into clinical decision making. Abundant immune infiltration in the tumor tissue is likely to have highprognostic value, but not an equally high predictive value interms of response to immunotherapy. The intrinsic characteristics of MSI and MSS CRCs determine differences in their evolutionary paths, which inevitably influence the way the immune system sculpts tumor clonal and subclonal dynamics. Immunotherapy with immune checkpoint inhibitors is an approved treatment option for a subpopulation of patients with colorectal cancers that display microsatellite instability. However, not all individuals within this subgroup respond to immunotherapy, and molecular biomarkers for effective patient stratification are still lacking. In this opinion article, we provide an overview of the different biological parameters that contribute to rendering colorectal cancers with microsatellite instability potentially sensitive to immunotherapy. We critically discuss the reasons why such parameters have limited predictive value and the implications therein. We also consider that a more informed knowledge of response determinants in this tumor subtype could help understand the mechanisms of immunotherapy resistance in microsatellite stable tumors. We conclude that the dynamic nature of the interactions between cancer and immune cells complicates conventional biomarker development and argue that a new generation of adaptive metrics, borrowed from evolutionary genetics, may improve the effectiveness and reliability of clinical decision making.

In this review, we discuss biomarkers of response and resistance to PI3K inhibitors (PI3Ki) in estrogen receptor-positive breast cancer, both in the early and advanced settings. We analyse data regarding PIK3CA mutations, PI3K pathway activation, PTEN expression loss, Akt signalling, insulin levels, 18FFDG-PET/CT imaging, FGFR1/2 amplification, KRAS and TP53 mutations. Most of the discussed data comprise retrospective and exploratory studies, hence many results are not conclusive. Therefore, among all of these biomarkers, only PIK3CA mutations have proved to have a predictive value for treatment with the α-selective PI3Ki alpelisib (SOLAR-1 trial) and the β-sparing PI3Ki taselisib (SANDPIPER trial) in the advanced setting. Since the accuracy of current individual biomarkers is not optimal, a composite biomarker, including DNA, RNA and protein expression data, to more precisely assess the PI3K/AKT/mTOR pathway activation status, may arise as a promising approach. Finally, we describe the rational for new combination therapies involving PI3Ki and anti-HER2 agents, chemotherapy, CDK4/6 inhibitors, mTOR inhibitors or new endocrine treatments and discuss the ongoing trials in this field., SCOPUS: ar.j, info:eu-repo/semantics/published

Five-year overall survival of stage III colorectal cancer (CRC) patients treated with standard adjuvant chemotherapy (ACHT) is highly variable. Genomic biomarkers and/or transcriptomic profiles identified lack of adequate validation. Aim of our study was to identify and validate molecular biomarkers predictive of ACHT response in stage III CRC patients by a transcriptomic approach. From a series of CRC patients who received ACHT, two stage III extreme cohorts (unfavorable vs. favorable prognosis) were selected. RNA-sequencing was performed from fresh frozen explants. Tumors were characterized for somatic mutations. Validation was performed in stage III CRC patients extracted from two GEO datasets. According to disease-free survival (DFS), 108 differentially expressed genes (104/4 up/downregulated in the unfavorable prognosis group) were identified. Among 104 upregulated genes, 42 belonged to olfactory signaling pathways, 62 were classified as pseudogenes (n = 17), uncharacterized noncoding RNA (n = 10), immune response genes (n = 4), microRNA (n = 1), cancer-related genes (n = 14) and cancer-unrelated genes (n = 16). Three out of four down-regulated genes were cancer-related. Mutational status (i.e., RAS, BRAF, PIK3CA) did not differ among the cohorts. In the validation cohort, multivariate analysis showed high PNN and KCNQ1OT1 expression predictive of shorter DFS in ACHT treated patients (p = 0.018 and p = 0.014, respectively); no difference was observed in untreated patients. This is the first study that identifies by a transcriptomic approach and validates PNN and KCNQ1OT1 as molecular biomarkers predictive of chemotherapy response in stage III CRC patients. After a further validation in an independent cohort, PNN and KCNQ1OT1 evaluation could be proposed to prospectively identify stage III CRC patients benefiting from ACHT.

Summary Characterizing likelihood of response to neoadjuvant chemotherapy (NAC) in muscle-invasive bladder cancer (MIBC) is an important yet unmet challenge. In this study, a machine-learning framework is developed using imaging of biopsy pathology specimens to generate models of likelihood of NAC response. Developed using cross-validation (evaluable N = 66) and an independent validation cohort (evaluable N = 56), our models achieve promising results (65%–73% accuracy). Interestingly, one model—using features derived from hematoxylin and eosin (H&E)-stained tissues in conjunction with clinico-demographic features—is able to stratify the cohort into likely responders in cross-validation and the validation cohort (response rate of 65% for predicted responder compared with the 41% baseline response rate in the validation cohort). The results suggest that computational approaches applied to routine pathology specimens of MIBC can capture differences between responders and non-responders to NAC and should therefore be considered in the future design of precision oncology for MIBC., Graphical abstract, Highlights Using imaging of pathology samples to predict chemotherapy response in bladder cancer Multi-modal integration of cell nuclear and tissue architectural features Models using H&E images and basic clinical features able to enrich for responders Predictive features suggest response-modulating factors in tumor microenvironment, Using multi-modal machine-learning leveraging features from digital pathology, Mi et al. develop models to predict response to chemotherapy in muscle-invasive bladder cancer. Models using handcrafted features derived from conventional H&E TMAs in conjunction with basic clinico-demographic features significantly stratify likelihood of response in both discovery and independent validation cohorts.

Numerous retrospective studies have demonstrated that the density of intra-tumoral immune cell infiltration is prognostic in epithelial ovarian cancer (OC). These observations together with reports of programmed death ligand-1 (PD-L1) expression in advanced OC provided the rationale for investigating the benefit of programmed death-1 (PD1) or PD-L1 inhibition in OC. Unfortunately clinical trials to date evaluating PD1/PD-L1 inhibition in patients with relapsed OC have been disappointing. In this review we will discuss early results from single agent PD1/PD-L1 inhibitors and the strategies to enhance benefit from immune-oncology agents in OC, including proposing anti-PD-L1 in combination with other agents (cytotoxics, anti-angiogenics, poly(ADP-ribose) polymerase. (PARP) inhibitors, targeted therapies or other immunotherapies), as well as evaluating these agents earlier in the disease course, or in biomarker selected patients.

Pembrolizumab has been approved as first-line treatment for advanced Non-small cell lung cancer (NSCLC) patients with tumors expressing PD-L1 and in the absence of other targetable alterations. However, not all patients that meet these criteria have a durable benefit. In this monocentric study, we aimed at refining the selection of patients based on the expression of immune genes. Forty-six consecutive advanced NSCLC patients treated with pembrolizumab in first-line setting were enrolled. The expression levels of 770 genes involved in the regulation of the immune system was analysed by the nanoString system. PD-L1 expression was evaluated by immunohistochemistry. Patients with durable clinical benefit had a greater infiltration of cytotoxic cells, exhausted CD8, B-cells, CD45, T-cells, CD8 T-cells and NK cells. Immune cell scores such as CD8 T-cell and NK cell were good predictors of durable response with an AUC of 0.82. Among the immune cell markers, XCL1/2 showed the better performance in predicting durable benefit to pembrolizumab, with an AUC of 0.85. Additionally, CD8A, CD8B and EOMES showed a high specificity (&gt, 0.86) in identifying patients with a good response to treatment. In the same series, PD-L1 expression levels had an AUC of 0.61. The characterization of tumor microenvironment, even with the use of single markers, can improve patients’ selection for pembrolizumab treatment.

Simple Summary Advanced prostate cancer remains currently an important cause of cancer death. Despite the emergence of new treatments during the last decade, their efficiency is limited due to therapeutic resistance of tumor cells. Extracellular vesicles are secreted by cells and play an important role in cell–cell communications. Their content is specific to the cell that produced them, and they can be isolated from biological fluids such as blood and urine. In this review, we highlight the recent results demonstrating the impact of extracellular vesicles in the mechanisms leading to therapeutic resistance and their use to find new predictive biomarkers in order to facilitate treatment decision and personalized medicine. Abstract Prostate cancer (PCa) is the second most frequent cancer and the fifth leading cause of cancer death among men worldwide. At first, advanced PCa is treated by androgen deprivation therapy with a good initial response. Nevertheless, recurrences occur, leading to Castrate-Resistance Prostate Cancer (CRPC). During the last decade, new therapies based on inhibition of the androgen receptor pathway or taxane chemotherapies have been used to treat CRPC patients leading to an increase in overall survival, but the occurrence of resistances limits their benefits. Numerous studies have demonstrated the implication of extracellular vesicles (EVs) in different cancer cellular mechanisms. Thus, the possibility to isolate and explore EVs produced by tumor cells in plasma/sera represents an important opportunity for the deciphering of those mechanisms and the discovery of biomarkers. Herein, we summarized the role of EVs in therapeutic resistance of advanced prostate cancer and their use to find biomarkers able to predict these resistances.

Antibody-drug conjugates (ADCs) represent a new class of highly potent antineoplastic drugs built by attaching a small molecule of an anticancer drug (payload) or another therapeutic agent to an antibody recognizing an epitope on the targeted cells. Trophoblast cell-surface antigen-2 (Trop-2) was originally described in trophoblasts and fetal tissues, but subsequently, its overexpression has been demonstrated in various solid malignancies. Sacituzumab govitecan, a conjugate of anti-Trop-2 antibody and SN-38 payload (an active metabolite of irinotecan), is the first in the class that has been clinically validated and approved by the Food and Drug Administration for the treatment of metastatic triple-negative breast (2020) and urothelial carcinomas (2021). In the current review, we summarize and critically appraise the most recent advances with Sacituzumab govitecan, emphasizing the predictive biomarker analysis.

A patient’s response to immune checkpoint inhibitors (ICIs) is a complex quantitative trait, and determined by multiple intrinsic and extrinsic factors. Three currently FDA-approved predictive biomarkers (progra1mmed cell death ligand-1 (PD-L1); microsatellite instability (MSI); tumor mutational burden (TMB)) are routinely used for patient selection for ICI response in clinical practice. Although clinical utility of these biomarkers has been demonstrated in ample clinical trials, many variables involved in using these biomarkers have poised serious challenges in daily practice. Furthermore, the predicted responders by these three biomarkers only have a small percentage of overlap, suggesting that each biomarker captures different contributing factors to ICI response. Optimized use of currently FDA-approved biomarkers and development of a new generation of predictive biomarkers are urgently needed. In this review, we will first discuss three widely used FDA-approved predictive biomarkers and their optimal use. Secondly, we will review four novel gene signature biomarkers: T-cell inflamed gene expression profile (GEP), T-cell dysfunction and exclusion gene signature (TIDE), melanocytic plasticity signature (MPS) and B-cell focused gene signature. The GEP and TIDE have shown better predictive performance than PD-L1, and PD-L1 or TMB, respectively. The MPS is superior to PD-L1, TMB, and TIDE. The B-cell focused gene signature represents a previously unexplored predictive biomarker to ICI response. Thirdly, we will highlight two combined predictive biomarkers: TMB+GEP and MPS+TIDE. These integrated biomarkers showed improved predictive outcomes compared to a single predictor. Finally, we will present a potential nucleic acid biomarker signature, allowing DNA and RNA biomarkers to be analyzed in one assay. This comprehensive signature could represent a future direction of developing robust predictive biomarkers, particularly for the cold tumors, for ICI response.

Background The Oncotype DX 21-gene Recurrence Score is predictive of adjuvant chemotherapy benefit for women with early-stage, estrogen receptor (ER)-positive, HER2-negative breast cancer. In premenopausal women, fluctuations in estrogen and progesterone during the menstrual cycle impact gene expression in hormone-responsive cancers. However, the extent to which menstrual cycling affects the Oncotype DX 21-gene signature remains unclear. Here, we investigate the impact of ovarian cycle stage on the 21-gene signature using a naturally cycling mouse model of breast cancer. Methods ER-positive mammary tumours were dissected from naturally cycling Mmtv-Pymt mice at either the estrus or diestrus phase of the ovarian cycle. The Oncotype DX 21-gene signature was assessed through quantitative real time-PCR, and a 21-gene experimental recurrence score analogous to the Oncotype DX Recurrence Score was calculated. Results Tumours collected at diestrus exhibited significant differences in expression of 6 Oncotype DX signature genes (Ki67, Ccnb1, Esr1, Erbb2, Grb7, Bag1; p ≤ 0.05) and a significant increase in 21-gene recurrence score (21.8 ± 2.4; mean ± SEM) compared to tumours dissected at estrus (15.5 ± 1.9; p = 0.03). Clustering analysis revealed a subgroup of tumours collected at diestrus characterised by increased expression of proliferation- (p p = 0.01) genes, and increased 21-gene recurrence score (p = 0.01). No correlation between ER, PR, HER2, and KI67 protein abundance measured by Western blot and abundance of mRNA for the corresponding gene was observed, suggesting that gene expression is more susceptible to hormone-induced fluctuation compared to protein expression. Conclusions Ovarian cycle stage at the time of tissue collection critically affects the 21-gene signature in Mmtv-Pymt murine mammary tumours. Further studies are required to determine whether Oncotype DX Recurrence Scores in women are similarly affected by menstrual cycle stage.

The rate of cognitive decline among patients with amnestic mild cognitive impairment (aMCI) varies, and it is thus crucial to accurately predict the probability of cognitive deterioration in patients with MCI. We compared the potential of cytokines with amyloid beta (Aβ) and tau biomarkers for predicting cognitive decline in patients with aMCI or Alzheimer’s disease (AD). All participants (controls, aMCI, and AD patients) underwent plasma biomarker examinations for Aβ1–40, Aβ1–42, total tau (t-tau), tau phosphorylated at threonine 181 [p-Tau181]), and 29 cytokines and baseline cognitive tests, including Mini-Mental State Examination (MMSE). The correlation between biomarker levels and annual MMSE change during the follow-up was examined. Receiver operating characteristic (ROC) curve analysis was performed to determine whether the statistically significant plasma biomarkers could identify cognitive decline. Higher baseline levels of IL-2, sCD40L, IL-8, and VEGF were associated with a lower annual cognitive decline in the aMCI group, and higher baseline levels of Aβ1–40, IFNγ, IL-5, IL-17A, IL-25, and FGF were associated with a rapid annual cognitive decline in the AD group. IL-2 had a high discriminatory capacity for identifying cognitive decline, with an area under curve (AUC) of 85.7% in the aMCI group, and the AUC was slightly increased when combining IL-2 with Aβ or tau biomarkers. However, none of the biomarkers had a satisfactory discriminatory capacity in the AD group. IL-2 may have a better discriminatory capacity for identifying cognitive decline than Aβ and tau biomarkers in patients with aMCI.

Oral leukoplakia (OL) has a propensity for recurrence and malignant transformation (MT). Herein, we evaluate sociodemographic, clinical, microscopic and immunohistochemical parameters as predictive factors for OL recurrence, also comparing primary lesions (PLs) with recurrences. Thirty-three patients with OL, completely removed either by excisional biopsy or by laser ablation following incisional biopsy, were studied. Selected molecules associated with the STAT3 oncogenic pathway, including pSTAT3, Bcl-xL, survivin, cyclin D1 and Ki-67, were further analyzed. A total of 135 OL lesions, including 97 PLs and 38 recurrences, were included. Out of 97 PLs, 31 recurred at least once and none of them underwent MT, during a mean follow-up time of 48.3 months. There was no statistically significant difference among the various parameters in recurrent vs. non-recurrent PLs, although recurrence was most frequent in non-homogeneous lesions (p = 0.087) and dysplastic lesions recurred at a higher percentage compared to hyperplastic lesions (34.5% vs. 15.4%). Lower levels of Bcl-xL and survivin were identified as significant risk factors for OL recurrence. Recurrences, although smaller and more frequently homogeneous and non-dysplastic compared to their corresponding PLs, exhibited increased immunohistochemical expression of oncogenic molecules, especially pSTAT3 and Bcl-xL. Our results suggest that parameters associated with recurrence may differ from those that affect the risk of progression to malignancy and support OL management protocols favoring excision and close monitoring of all lesions.

Cholangiocarcinoma (CCA) is an aggressive cancer type with a dismal prognosis. CCA typically presents at an advanced stage when surgical resection is not feasible, and systemic chemotherapy is generally of limited benefit. Thus, developing effective therapies against this deadly tumor is imperative and remains an unmet need. To provide more effective treatment options, high-throughput approaches have been employed, leading to a better delineation of each CCA subtype’s genomic and transcriptomic landscape as well as the identification of promising candidates for targeted, personalized therapies. In this scenario, the recent approval of pemigatinib, a pan-Fibroblast Growth Factor Receptor (FGFR) inhibitor, for the treatment of the CCA subtype characterized by FGFR2 mutations, represents the first of (presumably) numerous novel therapeutic approaches against this aggressive disease. AREAS COVERED: This review provides an overview regarding the current scenario and knowledge of the genomic landscape occurring in CCA and the potentially actionable molecular aberrations in each CCA subtype. EXPERT OPINION: The establishment and advances of high-throughput methodologies applied to genetic and epigenetic profiling are changing the therapeutic landscape of many cancer types, including CCA. These approaches have led to the generation of a large body of data that must be interpreted appropriately and eventually implemented in clinical practice. The following advancements towards precision medicine in CCA management will require designing better clinical trials with improved methods to stratify biliary tumor patients.

Background DNA methylation is associated with atherosclerosis and cardiovascular risk factors. However, little evidence regarding its association with cardiovascular diseases in large studies is currently available. We aimed to assess the association between DNA methylation and cardiovascular events, and to determine both the predictive capacity of the identified loci and the causality of those associations. Methods We defined two strategies: epigenome-wide (EWAS) and candidate-gene association studies. In both strategies, we designed one approach with prevalent cases of coronary heart disease (CHD) and another with incident cases of CHD and cardiovascular disease. We used data from three independent cohorts: the REgistre GIroní del COR (REGICOR) study, the Framingham Offspring Study and the Women’s Health Initiative. We also assessed the association between the identified CpGs and cardiovascular risk factors in the three populations. Then, we developed methylation risk scores to evaluate whether their inclusion in the Framingham risk function improved its predictive capacity. Finally, we performed a Mendelian randomization study to determine the causality of the identified associations. Results We found 17 CpGs related to prevalent CHD and/or incident cardiovascular events, two of them observed using both approaches ( p

Non-small-cell lung cancer (NSCLC) is a major cause of death worldwide. Alterations in such genes as EGFR and ALK are considered important biomarkers in NSCLC due to the existence of targeted therapies with specific tyrosine kinase inhibitors (TKIs). However, specific resistance-related mutations can occur during TKI treatment, which often result in therapy inefficacy. Liquid biopsies arise as a reliable tool for the early detection of these types of alterations, allowing a non-invasive follow-up of the patients. Furthermore, they can be essential for cancer screening, initial diagnosis and to check surgery success. Despite the great advantages of liquid biopsies in NSCLC and the high input that next-generation sequencing (NGS) approaches can provide in this field, its use in oncology is still limited. With improvement of assay sensitivity and the establishment of clinical guidelines for liquid biopsy analysis, it is expected that they will be used in routine procedures. This review focuses on the usefulness of liquid biopsies of NSCLC patients as a means to detect alterations in EGFR and ALK genes and in disease management, highlighting the impact of NGS methods.

Despite extensive research efforts, advanced gastric cancer still has a dismal prognosis with conventional treatment options. Immune checkpoint inhibitors have revolutionized the treatment landscape for many solid tumors. Amongst gastric cancer subtypes, tumors with microsatellite instability and Epstein Barr Virus positive tumors provide the strongest rationale for responding to immunotherapy. Various predictive biomarkers such as mismatch repair status, programmed death ligand 1 expression, tumor mutational burden, assessment of tumor infiltrating lymphocytes and circulating biomarkers have been evaluated. However, results have been inconsistent due to different methodologies and thresholds used. Clinical implementation therefore remains a challenge. The role of immune checkpoint inhibitors in gastric cancer is emerging with data from monotherapy in the heavily pre-treated population already available and studies in earlier disease settings with different combinatorial approaches in progress. Immune checkpoint inhibitor combinations with chemotherapy (CT), anti-angiogenics, tyrosine kinase inhibitors, anti-Her2 directed therapy, poly (ADP-ribose) polymerase inhibitors or dual checkpoint inhibitor strategies are being explored. Moreover, novel strategies including vaccines and CAR T cell therapy are also being trialed. Here we provide an update on predictive biomarkers for response to immunotherapy with an overview of their strengths and limitations. We discuss clinical trials that have been reported and trials in progress whilst providing an account of future steps needed to improve outcome in this lethal disease.

Background and aims Studies suggest that mutations in the CTNNB1 gene are predictive of response to immunotherapy, an emerging therapy for advanced hepatocellular carcinoma (HCC). Analysis of circulating tumor DNA (ctDNA) offers the possibility of serial non-invasive mutational profiling of tumors. Combining tumor tissue and ctDNA analysis may increase the detection rate of mutations. This study aimed to evaluate the frequency of the CTNNB1 p.T41A mutation in ctDNA and tumor samples from HCC patients and to evaluate the concordance rates between plasma and tissue. We further evaluated changes in ctDNA after various HCC treatment modalities and the impact of the CTNNB1 p.T41A mutation on the clinical course of HCC. Methods We used droplet digital PCR to analyze plasma from 95 patients and the corresponding tumor samples from 37 patients during 3 years follow up. Results In tumor tissue samples, the mutation rate was 8.1% (3/37). In ctDNA from HCC patients, the CTNNB1 mutation rate was 9.5% (9/95) in the pre-treatment samples. Adding results from plasma analysis to the subgroup of patients with available tissue samples, the mutation detection rate increased to 13.5% (5/37). There was no difference in overall survival according to CTNNB1 mutational status. Serial testing of ctDNA suggested a possible clonal evolution of HCC or arising multicentric tumors with separate genetic profiles in individual patients. Conclusion Combining analysis of ctDNA and tumor tissue increased the detection rate of CTNNB1 mutation in HCC patients. A liquid biopsy approach may be useful in a tailored therapy of HCC.

Background: EGFR, ERBB2, ERBB3, and ERBB4 are growth receptors of the ERBB family implicated in the development of epithelial cancers. Studies have suggested a role for EGFR and ERBB3 in the development of prostate cancer (PC), while the involvement of ERBB2 and ERBB4 remains unclear. In this study, we evaluated the expression of all members of the ERBB family in PC tissue from a large cohort and determined their contribution, alone or in combination, as prognostic markers. Methods: Using immunofluorescence coupled with digital image analyses, we quantified the expression of EGFR, ERBB2, ERBB3, and ERBB4 on radical prostatectomy specimens (n = 285) arrayed on six tissue microarrays. By combining EGFR, ERBB2, and ERBB3 protein expression in a decision tree model, we identified an association with biochemical recurrence (log rank = 25.295, p &lt, 0.001), development of bone metastases (log rank = 23.228, p &lt, 0.001), and cancer-specific mortality (log rank = 24.586, p &lt, 0.001). Conclusions: Our study revealed that specific protein expression patterns of ERBB family members are associated with an increased risk of PC progression and mortality.

We assessed the feasibility of adjuvant S-1 and oxaliplatin following neoadjuvant chemoradiotherapy (nCRT) and esophagectomy. Patients treated with nCRT (paclitaxel, carboplatin) and esophagectomy received six 21-day cycles with oxaliplatin (130 mg/m2) on day 1 and S-1 (25 mg/m2 twice daily) on days 1–14. The primary endpoint was feasibility, defined as ≥50% completing treatment. We performed exploratory propensity-score matching to compare survival, ERCC1 and Thymidylate Synthase (TS) immunohistochemistry analyses, proteomics biomarker discovery and 5-FU pharmacokinetic analyses. Forty patients were enrolled and 48% completed all adjuvant cycles. Median dose intensity was 98% for S-1 and 62% for oxaliplatin. The main reason for early discontinuation was toxicity (67%). The median recurrence-free and overall survival were 28.3 months and 40.8 months, respectively (median follow-up 29.1 months). Survival was not significantly prolonged compared to a matched cohort (p = 0.09). Patients with ERCC1 negative tumor expression had significantly better survival compared to ERCC1 positivity (p = 0.01). Our protein signature model was predictive of survival [p = 0.04, Area under the curve (AUC) 0.80]. Moreover, 5-FU pharmacokinetics significantly correlated with treatment-related toxicity. To conclude, six cycles adjuvant S-1 and oxaliplatin were not feasible in pretreated esophageal adenocarcinoma. Although the question remains whether additional treatment with chemotherapy should be provided in the adjuvant setting, subgroups such as patients with ERCC1 negativity could potentially benefit from adjuvant SOX based on our exploratory biomarker research.

Simple Summary Over the last decade, immune checkpoint inhibitors (ICIs) targeting programmed death 1 (PD-1), programmed death-ligand 1 (PD-L1), and cytotoxic T-lymphocyte antigen 4 (CTLA-4) have dramatically changed the therapeutic algorithm of several hematological and solid tumors. Of note, these agents have been also investigated in biliary tract cancer (BTC), reporting controversial results so far; in this setting, the role of ICIs is still to be established, and available data on immunotherapy in BTC patients are mainly limited to sub-analyses of basket trials and small single-arm studies. A crucial challenge is represented by the lack of validated predictive biomarkers, that could help identify responders to immunotherapy, a high unmet need in these immunologically “cold” malignancies where ICIs are still looking for their niche. Abstract Biliary tract cancer (BTC) represents the second most frequently diagnosed primary liver cancer worldwide following hepatocellular carcinoma, and the overall survival of patients with unresectable disease remains poor. In recent years, the advent of immune checkpoint inhibitors (ICIs) has revolutionized the therapeutic landscape of several malignancies with these agents, which have also been explored in advanced BTC, as monotherapy or in combination with other anticancer agents. However, clinical trials evaluating ICIs in BTC have shown conflicting results, and the clinical benefit provided by immunotherapy seems limited to a small subgroup of BTC patients. Thus, the identification of reliable predictors of the response to immunotherapy represents a significant challenge in this setting. This review provides an overview of the available evidence on the biomarkers predictive of the response to ICIs in patients with advanced BTC, especially focusing on programmed death-ligand 1 (PD-L1), tumor mutational burden (TMB), microsatellite instability (MSI), and other emerging biomarkers.

Immunotherapy has emerged as the fifth pillar of cancer treatment alongside surgery, radiotherapy, chemotherapy, and targeted therapy. Immune checkpoint inhibitors are the current superheroes of immunotherapy, unleashing a patient’s own immune cells to kill tumors and revolutionizing cancer treatment in a variety of cancers. Although breast cancer was historically believed to be immunologically silent, treatment with immune checkpoint inhibitors has been shown to induce modest responses in metastatic breast cancer. Given the inherent heterogeneity of breast tumors, this raised the question whether certain breast tumors might benefit more from immune-based interventions and which cancer cell-intrinsic and/or microenvironmental factors define the likelihood of inducing a potent and durable anti-tumor immune response. In this review, we will focus on triple negative breast cancer as immunogenic breast cancer subtype, and specifically discuss the relevance of tumor mutational burden, the plethora and diversity of tumor infiltrating immune cells in addition to the immunoscore, the presence of immune checkpoint expression, and the microbiome in defining immune checkpoint blockade response. We will highlight the current immune checkpoint inhibitor treatment options, either as monotherapy or in combination with standard-of-care treatment modalities such as chemotherapy and targeted therapy. In addition, we will look into the potential of immunotherapy-based combination strategies using immune checkpoint inhibitors to enhance both innate and adaptive immune responses, or to establish a more immune favorable environment for cancer vaccines. Finally, the review will address the need for unambiguous predictive biomarkers as one of the main challenges of immune checkpoint blockade. To conclude, the potential of immune checkpoint blockade for triple negative breast cancer treatment could be enhanced by exploration of aforementioned factors and treatment strategies thereby providing promising future prospects.

Simple Summary Immunotherapy has emerged as an attractive alternative to conventional therapies for the clinical management of prostate cancer (PCa); it not only specifically targets malignant cells while protecting healthy tissue, but it also appears to augment the therapeutic effect of existing treatments when used in combination. The identification of biomarkers with prognostic and preventive clinical significance has facilitated the incorporation of immune-targeted agents in clinical trials, with the aim to assess therapeutic efficacy in patient sub-populations that have been stratified on the basis of specific molecular traits and prognostic variables. This perfectly fits the rationale of precision medicine, which aims to match patients with targeted therapies so as to achieve the maximum clinical benefit. The numerous clinical trials currently evaluating multiple immunotherapeutic approaches in PCa patients, both alone and in combination with other treatments, offer much hope for achieving significant advances in the decision for precision treatment of the disease. Abstract Prostate cancer (PCa) is the most frequently diagnosed type of cancer among Caucasian males over the age of 60 and is characterized by remarkable heterogeneity and clinical behavior, ranging from decades of indolence to highly lethal disease. Despite the significant progress in PCa systemic therapy, therapeutic response is usually transient, and invasive disease is associated with high mortality rates. Immunotherapy has emerged as an efficacious and non-toxic treatment alternative that perfectly fits the rationale of precision medicine, as it aims to treat patients on the basis of patient-specific, immune-targeted molecular traits, so as to achieve the maximum clinical benefit. Antibodies acting as immune checkpoint inhibitors and vaccines entailing tumor-specific antigens seem to be the most promising immunotherapeutic strategies in offering a significant survival advantage. Even though patients with localized disease and favorable prognostic characteristics seem to be the ones that markedly benefit from such interventions, there is substantial evidence to suggest that the survival benefit may also be extended to patients with more advanced disease. The identification of biomarkers that can be immunologically targeted in patients with disease progression is potentially amenable in this process and in achieving significant advances in the decision for precision treatment of PCa.

Background: Characterization of tumor-related genetic alterations is promising for the screening of new predictive markers in non-small cell lung cancer (NSCLC). Aim of the study was to evaluate prognostic and predictive role of most frequent tumor-associated genetic alterations detected in plasma before starting immune checkpoint inhibitors (ICIs). Methods: Between January 2017 and October 2019, advanced NSCLC patients were prospectively screened with plasma next- generation sequencing (NGS) while included in two trials: VISION (NCT02864992), using Guardant360 (R) test, and MAGIC (Monitoring Advanced NSCLC through plasma Genotyping during Immunotherapy: Clinical feasibility and application), using Myriapod NGS-IL 56G Assay. A control group of patients not receiving ICIs was analyzed. Results: A total of 103 patients receiving ICIs were analyzed: median overall survival (OS) was 20.8 (95% CI: 16.7-24.9) months and median immune-related progression free disease (irPFS) 4.2 (95% CI: 2.3-6.1) months. TP53 mutations in plasma negatively affected OS both in patients treated with ICIs and in control group (P=0.001 and P=0.009), indicating a prognostic role. STK11 mutated patients (n=9) showed a trend for worse OS only if treated with ICIs. The presence of KRAS/STK11 co-mutation and KRAS/STK11/TP53 co-mutation affected OS only in patients treated with ICIs (HR =10.936, 95% CI: 2.337-51.164, P=0.002; HR =17.609, 95% CI: 3.777-82.089, P

We herein investigated the detection frequency and clinical relevance of circulating tumor cells (CTCs) in chemotherapy-na&iuml, ve stage IIIB/IV non-small cell lung cancer (NSCLC), by using the CellSearch and real-time CEACAM5mRNA assays. Blood samples from 43 patients were obtained at different time points during first-line chemotherapy. CellSearch revealed the detection of &ge, 1 CTCs in 41.9%, 40.9%, and 16.7% of patients at baseline, post-1st, and post-2nd treatment cycle, respectively, and of &ge, 5 CTCs in 11.6%, 9.1%, and 5.6%, respectively. CEACAM5mRNA+ CTCs were detected in 29.3% and 16% of patients pre- and post-treatment, respectively. The positivity concordance between the two assays was 2.2%. CTC-detection by CellSearch (&ge, 5 CTCs: p = 0.004), CEACAM5mRNA (p = 0.010), or by any assay (p = 0.000) was associated with disease progression. Reduced survival was demonstrated for patients harboring &ge, 5 CTCs (progression-free survival, PFS: p = 0.000, overall survival, OS: p = 0.009), CEACAM5mRNA+ CTCs (PFS: p = 0.043, OS: p = 0.039), and CTCs by any assay (PFS: p = 0.005, OS: p = 0.006, respectively). CTC-detection by any assay independently predicted for increased risk of relapse (hazard ratio, HR: 3.496, p = 0.001) and death (HR: 2.866, p = 0.008). CellSearch-positivity either pre-, post-1st, or post-2nd cycle, was predictive for shorter PFS (p = 0.036) compared to negativity in all time points. Persistent CEACAM5mRNA-positivity pre- and post-treatment was associated with reduced PFS (p = 0.036) and OS (p = 0.026). In conclusion, CTC detection and monitoring using the CellSearch and CEACAM5mRNA assays provides valuable and complementary clinical information for chemo-na&iuml, ve advanced or metastatic NSCLC.

Over the last few years efficacy of immunotherapy using immune checkpoint inhibitors (ICI) has been investigated in patients with bladder cancer (BC) at all stages. The present article aims to assess new therapeutic options with emerging agents in BC patients, shedding light on ICI-based treatments encompassing all disease stages, from non-muscle invasive (NMIBC) to muscle-invasive (MIBC) BC, concluding with metastatic MIBC. In bacillus Calmette-Guerin (BCG) unresponsive patients with carcinoma in situ, pembrolizumab has been recently approved. In the neoadjuvant setting, results from two clinical trials seem to identify pathological and genomic features of highly responsive tumors. Squamous cells and lymphoepithelioma/like histotypes, programmed cell-death ligand 1 (PD-L1) expression and high levels of activate T cells have been associated with higher response rate. In the metastatic setting, only 30% of patient may respond to ICI. A panel of biomarkers for patient selection is an actual need since the correlation between response and PD-L1 expression seem inconsistent across clinical trials, with some exceptions. Molecular characterization of BC, tumor mutation burden and immune-gene expression profiling might introduce new molecular biomarkers, hopefully transferable into the clinical-pathological practice.

Ovarian cancer (OC) remains a fatal malignancy because most patients experience recurrent disease, which is resistant to chemotherapy. The outcomes for patients with platinum-resistant OC are poor, response rates to further chemotherapy are low and median survival is lower than 12 months. The complexity of platinum-resistant OC, which comprises a heterogeneous spectrum of diseases, is indeed far from being completely understood. Therefore, comprehending tumors' biological behaviour to identify reliable biomarkers, which may predict responses to therapies, is a demanding challenge to improve OC management. In the age of precision medicine, efforts to overcome platinum resistance in OC represent a dynamic and vast field in which innovative drugs and clinical trials rapidly develop. This review will present the exceptional biochemical environment implicated in OC and highlights mechanisms of chemoresistance. Furthermore, innovative molecules and new therapeutic opportunities are presented, along with currently available therapies and ongoing clinical trials.

This review summarises the recent evidence on preoperative therapeutic strategies in pancreatic cancer and discusses the rationale for an imminent need for a personalised therapeutic approach in non-metastatic disease. The molecular diversity of pancreatic cancer and its influence on prognosis and treatment response, combined with the failure of ‘all-comer’ treatments to significantly impact on patient outcomes, requires a paradigm shift towards a genomic-driven approach. This is particularly important in the preoperative, potentially curable setting, where a personalised treatment allocation has the substantial potential to reduce pancreatic cancer mortality., Highlights • Molecular diversity of pancreatic cancer requires a paradigm shift towards a genomic-driven therapeutic approach. • Unselected treatment strategies demonstrate only limited efficacy in early-stage pancreatic cancer. • Personalised treatment in non-metastatic disease has potential to reduce pancreatic cancer mortality. • It is fundamental to implement preoperative clinical studies enriched for potential prognostic/predictive biomarkers. • Novel models of therapeutic development are warranted to accelerate progress in pancreatic cancer care and research.

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of lung cancer. However, their clinical benefit is limited to a minority of patients. To unravel immune-related factors that are predictive of sensitivity or resistance to immunotherapy, we performed a gene expression analysis by RNA-Seq using the Oncomine Immuno Response Assay (OIRRA) on a total of 33 advanced NSCLC patients treated with ICI evaluating the expression levels of 365 immune-related genes. We found four genes (CD1C, HLA-DPA1, MMP2, and TLR7) downregulated (p &lt, 0.05) and two genes (IFNB1 and MKI67) upregulated (p &lt, 0.05) in ICI-Responders compared to ICI-Non-Responders. The Bayesian enrichment computational analysis showed a more complex interaction network that involved 10 other genes (IFNA1, TLR4, CD40, TLR2, IL12A, IL12B, TLR9, CD1E, IFNG, and HLA-DPB1) correlated with different functional groups. Five main pathways were identified (FDR &lt, 0.0001). High TLR7 expression levels were significantly associated with a lack of response to immunotherapy (p &lt, 0.0001) and worse outcome in terms of both PFS (p &lt, 0.001) and OS (p = 0.03). The multivariate analysis confirmed TLR7 RNA expression as an independent predictor for both poor PFS (HR = 2.97, 95% CI, 1.16–7.6, p = 0.023) and OS (HR = 2.2, 95% CI, 1–5.08, p = 0.049). In conclusion, a high TLR7 gene expression level was identified as an independent predictor for poor clinical benefits from ICI. These data could have important implications for the development of novel single/combinatorial strategies TLR-mediated for an efficient selection of “individualized” treatments for NSCLC in the era of immunotherapy.

Simple Summary Soft tissue and bone sarcomas is a very heterogeneous group of tumors that has an aggressive course, especially in the metastatic setting. In this group the therapeutic options are rather limited. Immunotherapy is nowadays used successfully for the treatment of various tumor types. However in sarcomas this is still not the case. In this review article we aim to present all the available published information from clinical trials about the results of using immune checkpoint blockade as a therapeutic agent in sarcomas. Moreover, we try to unravel the possible prognostic biomarkers that may play here an important role. Soft tissue and bone sarcomas are a very heterogeneous group of tumors with many subtypes for which diagnosis and treatment remains a very challenging task. On top of that, the treatment choices are limited, and the prognosis of aggressive sarcomas remains poor. Immune checkpoint inhibitors (ICIs) have drawn a lot of attention last years because of their promising response rates and their durable effects. ICIs are currently widely used in the daily routine practice for the treatment of a different malignancies, such as melanoma, Hodgkin lymphoma, and non-small cell lung carcinoma. Still, ICIs are not included in the standard treatment protocols of the different sarcoma types. However, a plethora of clinical trials investigates the clinical benefit of ICIs in sarcomas. There is clear need to develop predictive biomarkers to determine which sarcoma patients are most likely to benefit from immune checkpoint blockade. This review will focus on (i) the clinical trial results on the use of ICIs in different sarcoma types; and on (ii) possible biomarkers predictive for the effectiveness of these drugs in sarcomas.

We investigated longitudinally the behaviour of anti-factor VIII (anti-FVIII) IgG subclasses for 6 months from inhibitor development in 43 patients from the Survey of Inhibitors in Plasma-Products Exposed Toddlers (SIPPET) trial who developed persistent or transient inhibitors. We first analysed 43 patients within 60 days post inhibitor detection. Then, 14 of these 43 patients were studied at five time points over 6 months. Our study showed that during the first 60 days, the risk of inhibitor persistence increased with the concomitant presence of an increasing number of IgG subclasses. Over the 6-month period post inhibitor detection, only the IgG2 subclass could be considered a hallmark of inhibitor persistence.