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According to the alarming statistical analysis of global cancer, there are over 19 million new diagnoses and more than 10 million deaths each year. One such cancer is the oral squamous cell carcinoma (OSCC), which requires new therapeutic strategies. Ficus septica extract has been used in traditional medicine to treat infectious diseases. In this study, we examined the anti-proliferative effects of an extract of F. septica bark (FSB) in OSCC cells. Our results showed that FSB caused a concentration-dependent reduction in the viability of SCC2095 OSCC cells, as determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assays, and was less sensitive to fibroblasts. In addition, FSB induced apoptosis by activating caspases, accompanied by the modulation of Akt/mTOR/NF-κB and mitogen-activated protein kinase signaling. Moreover, FSB increased reactive oxygen species generation in a concentration-dependent manner in SCC2095 cells. Furthermore, FSB inhibited cell migration and modulated the levels of the cell adhesion molecules including E-cadherin, N-cadherin, and Snail in SCC2095 cells. Pinoresinol, a lignan isolated from FSB, showed antitumor effects in SCC2095 cells, implying that this compound might play an important role in FSB-induced OSCC cell death. Taken together, FSB is a potential anti-tumor agent against OSCC cells.

The aims of this article are to examine how chatbots on Shaw’s works can be created through IBM artificial intelligence and cloud computing platform. The article will focus on a use case done by our Sagittarius Literature Digitizing Project: a Shaw Bot created on the IBM Cloud Computing Platform, to identify some best practices contributive to the creation of a literature bot, especially a theater bot. The article will also report on the pilot we did and some of the interesting findings. This project is a collaboration with the Shaw Festival and IBM Canada.

Prostate cancer, bladder cancer, and renal cancers are major urogenital cancers. Of which, prostate cancer is the most commonly diagnosed and second leading cause of cancer death for men in the United States. For urogenital cancers, urine is considered as proximate body fluid to the tumor site for developing non-invasiveness tests. However, the specific molecular signatures from different urogenital cancers are needed to relate changes in urine to various cancer detections. Herein, we utilized a previously published C4-Tip and C18/MAX-Tip workflow for enrichment of glycopeptides from urine samples and evaluated urinary glycopeptides for its cancer specificity. We analyzed 66 urine samples from bladder cancer (

Supplementary Figure S1. Computed Tomographic (CT) findings in patient CGLU116. Supplementary Figure S2. CT findings in patient CGLU127. Supplementary Figure S3. CT findings in patient CGLU161. Supplementary Figure S4. Tumor burden kinetics. Supplementary Figure S5. Neoantigen-specific TCR expansion in stimulated T cell cultures for patient CGLU127. Supplementary Figure S6. Neoantigen-specific TCR expansion in stimulated T cell cultures for patient CGLU161. Supplementary Figure S7. Loss of heterozygosity analyses for patient CGLU116. Supplementary Figure S8. Loss of heterozygosity analyses for patient CGLU117. Supplementary Figure S9. Loss of heterozygosity analyses for patient CGLU127. Supplementary Figure S10. Loss of heterozygosity analyses for patient CGLU161. Supplementary Figure S11. TCR clonality analyses for patients CGLU127 and CGLU161. Supplementary Figure S12. TCR clonality analyses for a responder and a non-responder to PD-1 blockade. Supplementary Figure S13. PD-L1 expression in responsive and resistant tumors. Supplementary Figure S14. Eliminated mutations for case CGHN2. Supplementary Figure S15. Comparison of five methods for estimation of tumor purity. Supplementary Figure S16. CD8+ T cell density in resistant tumors.

Supplementary Table S1. Summary of Patient and Sample Characteristics. Supplementary Table S2. Summary of Next-Generation Sequencing Analyses. Supplementary Table S3. Somatic Sequence Alterations*. Supplementary Table S4. Somatic Copy Number Alterations. Supplementary Table S5. Neoantigen Predictions. Supplementary Table S6. Characteristics of a Subset of Eliminated Candidate Neoantigens in the NSCLC patients*. Supplementary Table S7. Summary of Functionally Validated Eliminated, Gained, and Retained cMANAs. Supplementary Table S8. Eliminated MANA-specific T Cell Clonotypes in CGLU116, CGLU127 and CGLU161. Supplementary Table S9. Retained and Gained MANA-specific T Cell Clonotypes in CGLU116. Supplementary Table S10. Allelic Imbalance Analysis and Cellularity Estimates for CGLU116. Supplementary Table S11. Allelic Imbalance Analysis and Cellularity Estimates for CGLU117. Supplementary Table S12. Allelic Imbalance Analysis and Cellularity Estimates for CGLU127. Supplementary Table S13. Allelic Imbalance Analysis and Cellularity Estimates for CGLU161. Supplementary Table S14. Summary of Eliminated Neoantigens in NSCLC Cases. Supplementary Table S15. TCR-beta Sequencing Analysis. Supplementary Table S16. PD-L1 and CD8 Immunohistochemistry. Supplementary Table S17. Regions of Allelic Imbalance. Supplementary Table S18. Tumor Purity and Ploidy Estimates.

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Despite the initial successes of immunotherapy, there is an urgent clinical need for molecular assays that identify patients more likely to respond. Here, we report that ultrasensitive measures of circulating tumor DNA (ctDNA) and T-cell expansion can be used to assess responses to immune checkpoint blockade in metastatic lung cancer patients (N = 24). Patients with clinical response to therapy had a complete reduction in ctDNA levels after initiation of therapy, whereas nonresponders had no significant changes or an increase in ctDNA levels. Patients with initial response followed by acquired resistance to therapy had an initial drop followed by recrudescence in ctDNA levels. Patients without a molecular response had shorter progression-free and overall survival compared with molecular responders [5.2 vs. 14.5 and 8.4 vs. 18.7 months; HR 5.36; 95% confidence interval (CI), 1.57–18.35; P = 0.007 and HR 6.91; 95% CI, 1.37–34.97; P = 0.02, respectively], which was detected on average 8.7 weeks earlier and was more predictive of clinical benefit than CT imaging. Expansion of T cells, measured through increases of T-cell receptor productive frequencies, mirrored ctDNA reduction in response to therapy. We validated this approach in an independent cohort of patients with early-stage non–small cell lung cancer (N = 14), where the therapeutic effect was measured by pathologic assessment of residual tumor after anti-PD1 therapy. Consistent with our initial findings, early ctDNA dynamics predicted pathologic response to immune checkpoint blockade. These analyses provide an approach for rapid determination of therapeutic outcomes for patients treated with immune checkpoint inhibitors and have important implications for the development of personalized immune targeted strategies.Significance: Rapid and sensitive detection of circulating tumor DNA dynamic changes and T-cell expansion can be used to guide immune targeted therapy for patients with lung cancer.See related commentary by Zou and Meyerson, p. 1038

Supplementary Table S1. Summary of patient characteristics Supplementary Table S2. Summary of plasma samples analyzed Supplementary Table S3. Summary of peripheral blood lymphocytes and tumor infiltrating lymphocytes samples analyzed Supplementary Table S4. Genes analyzed by TEC-Seq Supplementary Table S5. Summary of TEC-Seq Characteristics Supplementary Table S6. Somatic sequence alterations detected in cfDNA Supplementary Table S7. Mutation Cellularity Analysis for tumor-specific cfDNA variants Supplementary Table S8. TCR-beta sequencing analysis Supplementary Table S9. Differentially abundant clones for CGLU111 Supplementary Table S10. Differentially abundant clones for CGLU117 Supplementary Table S11. Differentially abundant clones for CGLU127 Supplementary Table S12. Differentially abundant clones for CGLU212 Supplementary Table S13. Differentially abundant clones for CGLU135 Supplementary Table S14. Differentially abundant clones for CGLU161 Supplementary Table S15. Differentially abundant clones for CGLU159 Supplementary Table S16. Differentially abundant clones for CGLU162 Supplementary Table S17. Differentially abundant clones for CGLU203 Supplementary Table S18. Differentially abundant clones for CGLU243

Supplementary Figure S1. ctDNA clonal dynamics during anti-PD1 for patients with a clinical response. Supplementary Figure S2. ctDNA clonal dynamics during anti-PD1 for patients with molecular primary resistance. Supplementary Figure S3. ctDNA molecular responses precede radiologic responses. Supplementary Figure S4. Molecular responses correlate with a favorable prognosis. Supplementary Figure S5. Duration of molecular response correlates with progression-free and overall survival. Supplementary Figure S6. Disease prognostication by radiologic imaging at first assessment. Supplementary Figure S7. Differential clinical outcome by molecular responses in patients with radiologically stable disease. Supplementary Figure S8. Disease prognostication by tumor mutation burden. Supplementary Figure S9. ctDNA molecular response more accurately distinguish clinical responders from non-responders compared to clonal tumor mutation burden. Supplementary Figure S10. Molecular responses mirror pathologic responses to anti-PD1 therapy in early stage operable NSCLC. Supplementary Figure S11. TCR clonal dynamics during response and acquired resistance to anti-PD1. Supplementary Figure S12. TCR clonal dynamics for patients with clinical primary resistance. Supplementary Figure S13. Differential VJ gene usage for a patient with clinical response compared to a patient with clinical primary resistance. Supplementary Figure S14. Dynamic changes in pro-inflammatory and immunosuppressive cytokines in early stage NSCLC patients with differential responses to anti-PD1 therapy.

Supplementary Table and Figure Legends

Supplemental Table 1. Clinical and pathologic characteristics of patients included in tissue microarrays Supplementary Figure 1. B7-H4 expression is low in human and mouse lung cancer cell lines in vitro Supplementary Figure 2. B7-H1 expression does not change with MAPK or proliferation inhibition Supplementary Figure 3. Scoring of PD-L1 and pS6 staining in lung adenocarcinoma and squamous cell carcinoma TMAs Supplementary Figure 4. Co-expression of pS6 and PD-L1 staining in TMAs Supplemental Figure 5. The combination of rapamycin and anti-PD-1 antibody decreases KRAS-driven lung tumor growth Supplementary Figure 6. The combination of rapamycin and αPD-1 blockade decreases NNK-derived syngeneic lung tumor growth.

Alterations in EGFR, KRAS, and ALK are oncogenic drivers in lung cancer, but how oncogenic signaling influences immunity in the tumor microenvironment is just beginning to be understood. Immunosuppression likely contributes to lung cancer, because drugs that inhibit immune checkpoints like PD-1 and PD-L1 have clinical benefit. Here, we show that activation of the AKT–mTOR pathway tightly regulates PD-L1 expression in vitro and in vivo. Both oncogenic and IFNγ-mediated induction of PD-L1 was dependent on mTOR. In human lung adenocarcinomas and squamous cell carcinomas, membranous expression of PD-L1 was significantly associated with mTOR activation. These data suggest that oncogenic activation of the AKT–mTOR pathway promotes immune escape by driving expression of PD-L1, which was confirmed in syngeneic and genetically engineered mouse models of lung cancer where an mTOR inhibitor combined with a PD-1 antibody decreased tumor growth, increased tumor-infiltrating T cells, and decreased regulatory T cells. Cancer Res; 76(2); 227–38. ©2015 AACR.

Serum PSA, together with digital rectal examination and imaging of the prostate gland, have remained the gold standard in urological practices for the management of and intervention for prostate cancer. Based on these adopted practices, the limitations of serum PSA in identifying aggressive prostate cancer has led us to evaluate whether urinary PSA levels might have any clinical utility in prostate cancer diagnosis. Utilizing the Access Hybritech PSA assay, we evaluated a total of n = 437 urine specimens from post-DRE prostate cancer patients. In our initial cohort, PSA tests from a total of one hundred and forty-six (n = 146) urine specimens were obtained from patients with aggressive (Gleason Score ≥ 8, n = 76) and non-aggressive (Gleason Score = 6, n = 70) prostate cancer. A second cohort, with a larger set of n = 291 urine samples from patients with aggressive (GS ≥ 7, n = 168) and non-aggressive (GS = 6, n = 123) prostate cancer, was also utilized in our study. Our data demonstrated that patients with aggressive disease had lower levels of urinary PSA compared to the non-aggressive patients, while the serum PSA levels were higher in patients with aggressive prostate disease. The discordance between serum and urine PSA levels was further validated by immuno-histochemistry (IHC) assay in biopsied tumors and in metastatic lesions (n = 62). Our data demonstrated that aggressive prostate cancer was negatively correlated with the PSA in prostate cancer tissues, and, unlike serum PSA, urinary PSA might serve a better surrogate for capitulating tissue milieus to detect aggressive prostate cancer. We further explored the utility of urine PSA as a cancer biomarker, either alone and in combination with serum PSA, and their ratio (serum to urine PSA) to predict disease status. Comparing the AUCs for the urine and serum PSA alone, we found that urinary PSA had a higher predictive power (AUC= 0.732) in detecting aggressive disease. Furthermore, combining the ratios between serum to urine PSA with urine and serum assay enhanced the performance (AUC = 0.811) in predicting aggressive prostate disease. These studies support the role of urinary PSA in combination with serum for detecting aggressive prostate cancer.

The lack of access to and uptake of postpartum contraception is a key contributor to an estimated 121million unintended pregnancies worldwide. Research on counselling and women's preferences for postpartum contraception is scarce in Australia. We therefore aimed to explore Australian women's experiences of, and preferences for, accessing postpartum contraceptive counselling.In this qualitative study, English-speaking women of reproductive age (18-40years) with at least one child under the age of 5years were recruited via social media to participate in a semi-structured telephone interview. Interviews focussed on women's experiences of, and preferences for, postpartum contraception. The interviews were audio-recorded, transcribed, coded and thematically analysed.Twenty women participated. Most did not receive in-depth contraceptive counselling antenatally or postnatally, though had brief discussions with their GPs or obstetricians at the 6-week postnatal check. Participants felt some counselling throughout their antenatal and postnatal care would have been useful, particularly those who experienced medical complications perinatally. Most participants expressed a general preference for their GP or a midwife to provide such counselling, rather than an obstetrician or nurse, and they noted characteristics such as compassion, trust and care as being particularly important.The provision of postpartum contraceptive counselling could be enhanced in Australia. Contraceptive uptake in the postpartum period may be promoted by ensuring consistent and routine provision of contraceptive counselling for women antenatally and postnatally by their maternity carers.

Core fucosylation of N-linked glycoproteins has been linked to the functions of glycoproteins in physiological and pathological processes. However, quantitative characterization of core fucosylation remains challenging due to the complexity and heterogeneity of N-linked glycosylation. Here we report a mass spectrometry-based method that employs sequential treatment of intact glycopeptides with enzymes (STAGE) to analyze site-specific core fucosylation of glycoproteins. The STAGE method utilizes Endo F3 followed by PNGase F treatment to generate mass signatures for glycosites that are formerly modified by core fucosylated N-linked glycans. We benchmark the STAGE method and use it to characterize site specific core fucosylation of glycoproteins from human hepatocellular carcinoma and pancreatic ductal adenocarcinoma, resulting in the identification of 1130 and 782 core fucosylated glycosites, respectively. These results indicate that our STAGE method enables quantitative characterization of core fucosylation events from complex protein mixtures, which may benefit our understanding of core fucosylation functions in various diseases.

BACKGROUND In knowledge transfer for educational purposes, most cancer hospital/centre websites have existing information on cancer health. However, such information is usually a list of topics which are neither interactive nor offering any personal touches to people facing dire health crisis, not to say attempting to understand the concerns of the users. Cancer patients, their families and the general public accessing the information are often in challenging, stressful, situations, wanting to access accurate information as efficiently as possible. In addition, there is seldom any comprehensive information specifically on radiotherapy, despite the large number of cancer patients in senior ages, to go through the treatment process. Therefore, having “someone” with professional knowledge who can “listen” to them, provide the medical information with good will and encouragement would help patients and families struggling with critical illness, in particular during the lingering pandemic. OBJECTIVE The goal of this work is to create a virtual assistant, a chatbot that can explain the radiation treatment process in terms of the radiotherapy chain to stakeholders comprehensively and accurately. This virtual assistant was created using the IBM WATSON assistant with artificial intelligence (AI) and machine learning (ML) features. The chatbot or Bot was incorporated into a resource that can be easily accessed by the general public. METHODS The radiation treatment process in a cancer hospital/centre was described by the radiotherapy process: (1) patient diagnosis, consultation and prescription, (2) patient positioning, immobilization and simulation, (3) 3D imaging for treatment planning, (4) target and organ contouring, (5) radiation treatment planning, (6) patient setup and plan verification, and (7) treatment delivery. The Bot was created using IBM WATSON assistant. The natural language processing (NLP) feature in the WATSON platform allowed the Bot to flow through a given conversation structure and recognize how the user responds based on recognition of similar given examples, referred to as “intents” during development. The Bot therefore can be trained from the responses received, by recognizing similar responses from the user and analysed by the WATSON NLP. RESULTS The Bot is hosted on a website by the WATSON application programming interface (API). It is capable of guiding the user through the conversation structure and can respond to simple questions and provide resources for requests for information that was not directly programmed into the Bot. The Bot was tested by potential users and the overall averages of the identified metrics are excellent. The Bot can also acquire users’ feedbacks for further improvements in the routine update. CONCLUSIONS An AI-assisted chatbot was created for the knowledge transfer of radiation treatment process to the cancer patients, their families and general public. The Bot with character supported by ML was tested, and it was found that the bot can provide information in radiotherapy effectively. CLINICALTRIAL Nil

BackgroundDespite treatment advancements with immunotherapy, our understanding of response relies on tissue-based, static tumor features such as tumor mutation burden (TMB) and programmed death-ligand 1 (PD-L1) expression. These approaches are limited in capturing the plasticity of tumor–immune system interactions under selective pressure of immune checkpoint blockade and predicting therapeutic response and long-term outcomes. Here, we investigate the relationship between serial assessment of peripheral blood cell counts and tumor burden dynamics in the context of an evolving tumor ecosystem during immune checkpoint blockade.MethodsUsing machine learning, we integrated dynamics in peripheral blood immune cell subsets, including neutrophil-lymphocyte ratio (NLR), from 239 patients with metastatic non-small cell lung cancer (NSCLC) and predicted clinical outcome with immune checkpoint blockade. We then sought to interpret NLR dynamics in the context of transcriptomic and T cell repertoire trajectories for 26 patients with early stage NSCLC who received neoadjuvant immune checkpoint blockade. We further determined the relationship between NLR dynamics, pathologic response and circulating tumor DNA (ctDNA) clearance.ResultsIntegrated dynamics of peripheral blood cell counts, predominantly NLR dynamics and changes in eosinophil levels, predicted clinical outcome, outperforming both TMB and PD-L1 expression. As early changes in NLR were a key predictor of response, we linked NLR dynamics with serial RNA sequencing deconvolution and T cell receptor sequencing to investigate differential tumor microenvironment reshaping during therapy for patients with reduction in peripheral NLR. Reductions in NLR were associated with induction of interferon-γ responses driving the expression of antigen presentation and proinflammatory gene sets coupled with reshaping of the intratumoral T cell repertoire. In addition, NLR dynamics reflected tumor regression assessed by pathological responses and complemented ctDNA kinetics in predicting long-term outcome. Elevated peripheral eosinophil levels during immune checkpoint blockade were correlated with therapeutic response in both metastatic and early stage cohorts.ConclusionsOur findings suggest that early dynamics in peripheral blood immune cell subsets reflect changes in the tumor microenvironment and capture antitumor immune responses, ultimately reflecting clinical outcomes with immune checkpoint blockade.

Background The identification of differentially expressed tumor-associated proteins and genomic alterations driving neoplasia is critical in the development of clinical assays to detect cancers and forms the foundation for understanding cancer biology. One of the challenges in the analysis of pancreatic ductal adenocarcinoma (PDAC) is the low neoplastic cellularity and heterogeneous composition of bulk tumors. To enrich neoplastic cells from bulk tumor tissue, coring, and laser microdissection (LMD) sampling techniques have been employed. In this study, we assessed the protein and KRAS mutation changes associated with samples obtained by these enrichment techniques and evaluated the fraction of neoplastic cells in PDAC for proteomic and genomic analyses. Methods Three fresh frozen PDAC tumors and their tumor-matched normal adjacent tissues (NATs) were obtained from three sampling techniques using bulk, coring, and LMD; and analyzed by TMT-based quantitative proteomics. The protein profiles and characterizations of differentially expressed proteins in three sampling groups were determined. These three PDACs and samples of five additional PDACs obtained by the same three sampling techniques were also subjected to genomic analysis to characterize KRAS mutations. Results The neoplastic cellularity of eight PDACs ranged from less than 10% to over 80% based on morphological review. Distinctive proteomic patterns and abundances of certain tumor-associated proteins were revealed when comparing the tumors and NATs by different sampling techniques. Coring and bulk tissues had comparable proteome profiles, while LMD samples had the most distinct proteome composition compared to bulk tissues. Further genomic analysis of bulk, cored, or LMD samples demonstrated that KRAS mutations were significantly enriched in LMD samples while coring was less effective in enriching for KRAS mutations when bulk tissues contained a relatively low neoplastic cellularity. Conclusions In addition to bulk tissues, samples from LMD and coring techniques can be used for proteogenomic studies. The greatest enrichment of neoplastic cellularity is obtained with the LMD technique.

Background Here, we investigated radiological responses following chemotherapy alone as compared to both radiation/chemotherapy (chemoRT) in patients with thymic epithelial tumors (TETs) who did not receive upfront surgery. Methods TETs treated at a tertiary academic cancer center between January 2007 and July 2018 were identified. Patients received chemotherapy or chemoRT as initial therapy and pre‐ and post‐treatment scans were available. Student's t‐test, Wilcoxon rank‐sum tests, and Cox proportional hazards method were used to compare clinical details and survival between groups. The primary outcome was change in tumor size, which was compared between groups using linear mixed‐effects regression models, adjusting for baseline tumor size, age, and histology. Results A total of 24 of 114 patients with TETs identified met the inclusion criteria. The majority of patients had 67% thymoma (67%, n = 16) and AJCC8 III–IVA disease (58%, n = 14). Median age was 58.5 years (range: 33–76), median initial tumor volume was 187.1 cc (range: 28.7–653.6) and diameter was 8.5 cm (range: 4.5–14.3). Half of the patients received upfront chemotherapy (n = 12: 83% cisplatin/adriamycin/cyclophosphamide) or chemoRT (n = 12: 58% carboplatin/paclitaxel; median RT dose: 63 Gy [range: 60–70 Gy]). At a median imaging follow‐up of 15 months (range: 0–86): ChemoRT was associated with increased average radiological response compared to chemotherapy alone (volume: −47.0 cc more, P, ChemoRT was associated with a greater radiologic response than chemotherapy alone in patients with upfront unresectable TET

Background Prostate cancer (PCa) is a heterogeneous group of tumors, including non-aggressive (NAG) and aggressive (AG) subtypes, with variable clinical outcomes. We assessed the diagnostic utility of selected protein markers to identify AG tumors. Methods The TMA was constructed, including NAG and AG. 12 protein markers were evaluated using the TMA by IHC stains. The makers were also evaluated for their potential utility as single or panels for distinguishing AG from NAG tumors. Results The higher expressions of four protein markers, including prostate specific membrane antigen (PSMA), phospho-EGFR, androgen receptor (AR), and P16, were identified in AG tumors of Gleason score 4 and 5. In contrast, Galectin-3, DPP4 and MAN1B1 revealed stronger staining patterns in NAG tumors. Sensitivity and specificity of individual marker varied widely. In tow-marker panels, especially in the panel of DPP4 and PSMA, the specificity was 38.46% at 95% sensitivity. To further improve the detection ability, we combined DPP4 and PSMA with either Galectin-3 or phospho-EGFR into three-marker panels. The specificity achieved >46% at 95% sensitivity and AUC was >0.85. Conclusions Our panels can be used to improve the separation of AG from NAG tumor and to add in the optimization of the treatment strategy for patients.

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

Oligodendroglioma is a subtype of diffuse glioma defined by a mutation in the isocitrate dehydrogenase (IDH) genes and a co-deletion of chromosome arms 1p and 19q. These tumors primarily occur in adult patients in their third and fourth decade of life and are universally fatal due to an inevitable recurrence that follows a treatment regimen of surgical resection and an optional combination of alkylating chemotherapy and/or radiation therapy. While initially slow growing, recurrent tumors exhibit increasingly aggressive phenotypes that become progressively more difficult to treat with conventional therapy. Currently, the molecular mechanisms and cellular phenotypes that drive this recurrence remain unknown. To understand these factors, we assembled a cohort of matched initial and recurrent oligodendroglioma samples from over 100 patients and performed whole-genome sequencing and whole-exome sequencing on each of them. To link these molecular profiles to cell state changes, we additionally performed bulk and single-nucleus RNA-sequencing on a subset of these tumor pairs. In nearly 40% of alkylating chemotherapy-treated patients, recurrent tumors presented with hypermutation that corresponded with an increase in neoplastic cell proliferation. Additionally, while individual somatic alterations specific to recurrence were relatively rare, we observed a subset of tumors that acquired deletions in the cell cycle regulator CDKN2A following treatment with radiotherapy. Acquisition of either of these features associated with shorter patient survival and higher grade at recurrence, implicating cell cycle dysregulation as a mechanism of treatment resistance and increased tumor severity. Together, these results indicate that oligodendrogliomas evolve in a treatment-specific manner following chemo- and radiation therapy and highlight key pathways that can be targeted to delay the onset of recurrence.

Prostate cancer (PCa) is a heterogeneous group of tumors with variable clinical courses. In order to improve patient outcomes, it is critical to clinically separate aggressive PCa (AG) from non-aggressive PCa (NAG). Although recent genomic studies have identified a spectrum of molecular abnormalities associated with aggressive PCa, it is still challenging to separate AG from NAG. To better understand the functional consequences of PCa progression and the unique features of the AG subtype, we studied the proteomic signatures of primary AG, NAG and metastatic PCa. 39 PCa and 10 benign prostate controls in a discovery cohort and 57 PCa in a validation cohort were analyzed using a data-independent acquisition (DIA) SWATH–MS platform. Proteins with the highest variances (top 500 proteins) were annotated for the pathway enrichment analysis. Functional analysis of differentially expressed proteins in NAG and AG was performed. Data was further validated using a validation cohort; and was also compared with a TCGA mRNA expression dataset and confirmed by immunohistochemistry (IHC) using PCa tissue microarray (TMA). 4,415 proteins were identified in the tumor and benign control tissues, including 158 up-regulated and 116 down-regulated proteins in AG tumors. A functional analysis of tumor-associated proteins revealed reduced expressions of several proteinases, including dipeptidyl peptidase 4 (DPP4), carboxypeptidase E (CPE) and prostate specific antigen (KLK3) in AG and metastatic PCa. A targeted analysis further identified that the reduced expression of DPP4 was associated with the accumulation of DPP4 substrates and the reduced ratio of DPP4 cleaved peptide to intact substrate peptide. Findings were further validated using an independently-collected tumor cohort, correlated with a TCGA mRNA dataset, and confirmed by immunohistochemical stains of PCa tumor microarray (TMA). Our study is the first large-scale proteomics analysis of PCa tissue using a DIA SWATH-MS platform. It provides not only an interrogative proteomic signature of PCa subtypes, but also indicates the critical roles played by certain proteinases during tumor progression. The spectrum map and protein profile generated in the study can be used to investigate potential biological mechanisms involved in PCa and for the development of a clinical assay to distinguish aggressive from indolent PCa.

Summary Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.

Despite progress in immunotherapy, identifying patients that respond has remained a challenge. Through analysis of whole-exome and targeted sequence data from 5,449 tumors, we found a significant correlation between tumor mutation burden (TMB) and tumor purity, suggesting that low tumor purity tumors are likely to have inaccurate TMB estimates. We developed a new method to estimate a corrected TMB (cTMB) that was adjusted for tumor purity and more accurately predicted outcome to immune checkpoint blockade (ICB). To identify improved predictive markers together with cTMB, we performed whole-exome sequencing for 104 lung tumors treated with ICB. Through comprehensive analyses of sequence and structural alterations, we discovered a significant enrichment in activating mutations in receptor tyrosine kinase (RTK) genes in nonresponding tumors in three immunotherapy treated cohorts. An integrated multivariable model incorporating cTMB, RTK mutations, smoking-related mutational signature and human leukocyte antigen status provided an improved predictor of response to immunotherapy that was independently validated.

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer, comprising approximately 75% of all kidney tumors. Recent the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) studies have significantly advanced the molecular characterization of RCC and facilitated the development of targeted therapies. Such advances have improved the median survival of patients with advanced disease from less than 10 months prior to 2004 to 30 months by 2011. However, approximately 30% of localized ccRCC patients will nevertheless develop recurrence or metastasis after surgical resection of their tumor. Therefore, it is critical to further analyze potential tumor-associated proteins and their profiles during disease progression. Over the past decade, tremendous effort has been focused on the study of molecular pathways, including genomics, transcriptomics, and proteomics in order to identify potential molecular biomarkers, as well as to facilitate early detection, monitor tumor progression and uncover potentially therapeutic targets. In this review, we focus on recent advances in the proteomic analysis of ccRCC, current strategies and challenges, and perspectives in the field. This insight will highlight the discovery of tumor-associated proteins, and their potential clinical impact on personalized precision-based care in ccRCC.

Despite the initial successes of immunotherapy, there is an urgent clinical need for molecular assays that identify patients more likely to respond. Here, we report that ultrasensitive measures of circulating tumor DNA (ctDNA) and T-cell expansion can be used to assess responses to immune checkpoint blockade in metastatic lung cancer patients (N = 24). Patients with clinical response to therapy had a complete reduction in ctDNA levels after initiation of therapy, whereas nonresponders had no significant changes or an increase in ctDNA levels. Patients with initial response followed by acquired resistance to therapy had an initial drop followed by recrudescence in ctDNA levels. Patients without a molecular response had shorter progression-free and overall survival compared with molecular responders [5.2 vs. 14.5 and 8.4 vs. 18.7 months; HR 5.36; 95% confidence interval (CI), 1.57–18.35; P = 0.007 and HR 6.91; 95% CI, 1.37–34.97; P = 0.02, respectively], which was detected on average 8.7 weeks earlier and was more predictive of clinical benefit than CT imaging. Expansion of T cells, measured through increases of T-cell receptor productive frequencies, mirrored ctDNA reduction in response to therapy. We validated this approach in an independent cohort of patients with early-stage non–small cell lung cancer (N = 14), where the therapeutic effect was measured by pathologic assessment of residual tumor after anti-PD1 therapy. Consistent with our initial findings, early ctDNA dynamics predicted pathologic response to immune checkpoint blockade. These analyses provide an approach for rapid determination of therapeutic outcomes for patients treated with immune checkpoint inhibitors and have important implications for the development of personalized immune targeted strategies. Significance: Rapid and sensitive detection of circulating tumor DNA dynamic changes and T-cell expansion can be used to guide immune targeted therapy for patients with lung cancer. See related commentary by Zou and Meyerson, p. 1038

Purpose To describe a notable response to chemoradiation in a patient with locally advanced squamous cell cancer of the urethra. Materials and Methods Records reviewed of 60-year-old man with 15.3cm squamous cell cancer of the urethra. Treatment response assessed radiographically and pathologically, and post-treatment clinical status determined. Results Patient received 73.8 Gy plus concurrent cisplatin and 5-FU, followed by consolidative surgery. Patient had pathological complete response and remains radiographically disease-free at 28 months. Conclusion Consolidative surgery may be unnecessary even for large squamous cell carcinomas of the urethra following chemoradiation.

BackgroundProstate cancer (PCa) is a heterogeneous group of tumors with variable clinical courses. Clinically, it is critical to separate and treat aggressive PCa (AG) from non-aggressive PCa (NAG). Although recent genomic studies have identified a spectrum of molecular abnormalities associated with PCa, it is still challenge to separate AG from NAG. To better understand the functional consequence of PCa progression and the unique features of AG from NAG, we studied proteomic signatures of primary AG, NAG and metastatic PCa.Methodes39 PCa and 10 benign prostate controls in discovery cohort and 57 PCa in independent-collected validation cohort were analyzed using data-independent acquisition (DIA) SWATH–MS platform. Proteins with the highest variances (top 500 proteins) were annotated for the pathway enrichment analysis. Functional analysis of differentially expressed proteins in NAG and AG was performed. Data was further validated using validation cohort, as well as by comparison with TCGA mRNA expression and immnunochemistry on PCa tissue microarray (TMA).Results4,415 proteins were identified in the tumor and benign control tissues, including 158 up-regulated and 116 down-regulated proteins in AG tumors. A functional analysis of tumor-associated proteins revealed the reduced expression of several proteinases, including dipeptidyl peptidase 4 (DPP4), carboxypeptidase E (CPE) and prostate specific antigen (KLK3) in AG and metastatic PCa. A targeted analysis using SWATH data further identified that the reduced expression of DPP4 was associated with the accumulation of DPP4 substrates in AG tumors, including the reduced ratio of DPP4 cleaved peptide to intact substrate peptide. Findings were further validated using independent-collected cohort, by comparison with TCGA mRNA data, and the immunochemical stains of our tumor microarray (TMA).ConclusionsOur study is the first large-scale proteomics analysis of PCa tissue using DIA SWATH-MS platform. It not only provides an interrogative proteomic signature of PCa subtypes, but also indicates critical roles of certain proteinases, especially DPP4, in PCa progression. The spectrum map and protein profile generated in the study can be used to investigate potential biological mechanisms involved in the PCa progression as well as for the development of a clinical assay to distinguish aggressive from indolent PCa.

BACKGROUND Chatbot is a timely topic applied in various fields, including medicine and health care, for human-like knowledge transfer and communication. Machine learning, a subset of artificial intelligence, has been proven particularly applicable in health care, with the ability for complex dialog management and conversational flexibility. OBJECTIVE This review article aims to report on the recent advances and current trends in chatbot technology in medicine. A brief historical overview, along with the developmental progress and design characteristics, is first introduced. The focus will be on cancer therapy, with in-depth discussions and examples of diagnosis, treatment, monitoring, patient support, workflow efficiency, and health promotion. In addition, this paper will explore the limitations and areas of concern, highlighting ethical, moral, security, technical, and regulatory standards and evaluation issues to explain the hesitancy in implementation. METHODS A search of the literature published in the past 20 years was conducted using the IEEE Xplore, PubMed, Web of Science, Scopus, and OVID databases. The screening of chatbots was guided by the open-access Botlist directory for health care components and further divided according to the following criteria: diagnosis, treatment, monitoring, support, workflow, and health promotion. RESULTS Even after addressing these issues and establishing the safety or efficacy of chatbots, human elements in health care will not be replaceable. Therefore, chatbots have the potential to be integrated into clinical practice by working alongside health practitioners to reduce costs, refine workflow efficiencies, and improve patient outcomes. Other applications in pandemic support, global health, and education are yet to be fully explored. CONCLUSIONS Further research and interdisciplinary collaboration could advance this technology to dramatically improve the quality of care for patients, rebalance the workload for clinicians, and revolutionize the practice of medicine.

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment. Wang et al. perform integrated proteogenomic analysis of adult glioblastoma (GBM), including metabolomics, lipidomics, and single nuclei RNA-Seq, revealing insights into the immune landscape of GBM, cell-specific nature of EMT signatures, histone acetylation in classical GBM, and the existence of signaling hubs which could provide therapeutic vulnerabilities.