Search

Introduction: Osteosarcoma (OS) is a malignancy of the bone that mainly afflicts younger individuals. Despite existing treatment approaches, patients with metastatic or recurrent disease generally face poor prognoses. A greater understanding of the tumor microenvironment (TME) is critical for enhancing outcomes in OS patients. Methods: The clinical and RNA expression data of OS patients were extracted from the TARGET database. The single-cell RNA sequencing (scRNA-seq) data of 11 OS samples was retrieved from the GEO database, and analyzed using the Seurat package of R software. Copy number variation (CNV) was analyzed using the InferCNV software. The potential interactions between the different cells in the TME was analyzed with the CellChat package. A multi-algorithm-based computing framework was used to calculate the tumor-infiltrating immune cell (TIIC) scores. A prognostic model was constructed using 20 machine learning algorithms. Maftools R package was used to characterize the genomic variation landscapes in the patient groups stratified by TIIC score. The human OS cell lines MG63 and U2OS were used for the functional assays. Cell proliferation and migration were analyzed by the EdU assay and Transwell assay respectively. CLK1 protein expression was measured by immunoblotting. Results: We observed higher CNV in the OS cells compared to endothelial cells. In addition, there was distinct transcriptional heterogeneity across the OS cells, and cluster 1 was identified as the terminal differentiation state. S100A1, TMSB4X, and SLPI were the three most significantly altered genes along with the pseudo-time trajectory. Cell communication analysis revealed an intricate network between S100A1+ tumor cells and other TME cells. Cluster 1 exhibited significantly higher aggressiveness features, which correlated with worse clinical outcomes. A prognostic model was developed based on TIIC-related genes that were screened using machine learning algorithms, and validated in multiple datasets. Higher TIIC signature score was associated with lower cytotoxic immune cell infiltration and generally inferior immune response and survival rate. Moreover, TIIC signature score was further validated in the datasets of other cancers. CLK1 was identified as a potential oncogene that promotes the proliferation and migration OS cells. Conclusion: A TIIC-based gene signature was developed that effectively predicted the prognosis of OS patients, and was significantly associated with immune infiltration and immune response. Moreover, CLK1 was identified as an oncogene and potential therapeutic target for OS. [ABSTRACT FROM AUTHOR]

Background: Breast cancer (BC) is the most common cancer in women. Likewise, canine mammary tumors (CMT) represent the most common cancer in intact female dogs and develop in the majority spontaneously. Similarities exist in clinical presentation, histopathology, biomarkers, and treatment. However, CMT subtype-specific genomic background is less investigated. Here, we assess the genetic etiology of two histomorphological (HM) subtypes with BC counterparts, the CMT invasive ductal simple solid carcinoma (SC) and comedocarcinoma (CC), and compare the results with BC data. Methods: Groups of 11–13 transformed ductal luminal epithelial cells were laser-capture microdissected from snap-frozen invasive mammary SC and CC subtypes of one intact female dog. HM unaffected lobular luminal epithelial cells were controls. Single-cell whole genome libraries were generated using PicoPLEX and sequenced to compare the subtypes' somatic coding variant landscapes with each other and with BC data available in COSMIC-CGC and KEGG. Furthermore, HM and immunohistochemical (IHC) subtype characteristics were compared with the genomic results. Results: The CC had six times more variants than the SC. The SC showed variants in adherens junction genes and genes of the MAPK, mTOR and NF-kappa-B signaling pathways. In the CC, the extracellular matrix (ECM) receptor interaction, cell adhesion, PI3K-Akt and cGMP-PKG pathways were enriched, reflecting the higher cellular malignancy. Affected pathways in both CMT subtypes overlapped with BC pathways in KEGG. Additionally, we identified ATP6V1C2, GLYATL3, CARMIL3, GATAD2B, OBSCN, SIX2, CPEB3 and ZNF521 as potential new subtype-distinct driver genes. Furthermore, our results revealed biomarker alterations in IHC in the basal/myoepithelial cell layer without respective genetic mutations, suggesting changes to their complex signaling pathways, disturbed regulative feedback loops or other silencing mechanisms. Conclusions: This study contributes to understanding the subtype-specific molecular mechanisms in the canine mammary invasive ductal simple SC and CC, and revealed subtype-specific molecular complexity for phenotypically similar characteristics. Several affected genes and signaling pathways overlapped with BC indicating the potential use of CMT as model for BC. Our findings emphasize the need for thorough characterization of cancer specimens with respect to translational cancer research, but also how insight into tumor heterogeneity will be crucial for the development of targeted prognostics and therapeutic interventions. [ABSTRACT FROM AUTHOR]

This study explored the intratumor heterogeneity (ITH) of esophageal squamous cell carcinoma (ESCC) using computed tomography (CT) and investigated the value of CT-based ITH in predicting the response to immune checkpoint inhibitor (ICI) plus chemotherapy in patients with ESCC. This retrospective study included 416 patients with ESCC who received ICI plus chemotherapy at two independent hospitals between January 2019 and July 2022. Multiparametric CT features were extracted from ESCC lesions and screened using hierarchical clustering and dimensionality reduction algorithms. Logistic regression and machine learning models based on selected features were developed to predict treatment response and validated in separate datasets. ITH was quantified using the score calculated by the best-performing model and visualized through feature clustering and feature contribution heatmaps. A gene set enrichment analysis (GSEA) was performed to identify the biological pathways underlying the CT-based ITH. The extreme gradient boosting model based on CT-derived ITH had higher discriminative power, with areas under the receiver operating characteristic curve of 0.864 (95% confidence interval [CI]: 0.774–0.954) and 0.796 (95% CI: 0.698–0.893) in the internal and external validation sets. The CT-based ITH pattern differed significantly between responding and non-responding patients. The GSEA indicated that CT-based ITH was associated with immunity-, keratinization-, and epidermal cell differentiation-related pathways. CT-based ITH is an effective biomarker for identifying patients with ESCC who could benefit from ICI plus chemotherapy. Immunity-, keratinization-, and epidermal cell differentiation-related pathways may influence the patient's response to ICI plus chemotherapy. [ABSTRACT FROM AUTHOR]

Abstract Background Intratumor heterogeneity (ITH) is a key biological characteristic of gliomas. This study aimed to characterize ITH in adult-type diffuse gliomas and assess the feasibility of using habitat imaging based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) to preoperatively predict isocitrate dehydrogenase (IDH) genotypes and prognosis. Methods Sixty-three adult-type diffuse gliomas with known IDH genotypes were enrolled. Volume transfer constant (Ktrans) and apparent diffusion coefficient (ADC) maps were acquired from DCE-MRI and DWI, respectively. After tumor segmentation, the k-means algorithm clustered Ktrans and ADC image voxels to generate spatial habitats and extract quantitative image features. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were used to evaluate IDH predictive performance. Multivariable logistic regression models were constructed and validated using leave-one-out cross-validation, and the contrast-enhanced subgroup was analyzed independently. Kaplan-Meier and Cox proportional hazards regression analyses were used to investigate the relationship between tumor habitats and progression-free survival (PFS) in the two IDH groups. Results Three habitats were identified: Habitat 1 (hypo-vasopermeability and hyper-cellularity), Habitat 2 (hypo-vasopermeability and hypo-cellularity), and Habitat 3 (hyper-vasopermeability). Compared to the IDH wild-type group, the IDH mutant group exhibited lower mean Ktrans values in Habitats 1 and 2 (both P

Abstract Background Intratumoral heterogeneity emerges from accumulating genetic and epigenetic changes during tumorigenesis, which may contribute to therapeutic failure and drug resistance. However, the lack of a quick and convenient approach to determine the intratumoral epigenetic heterogeneity (eITH) limit the application of eITH in clinical settings. Here, we aimed to develop a tool that can evaluate the eITH using the DNA methylation profiles from bulk tumors. Methods Genomic DNA of three laser micro-dissected tumor regions, including digestive tract surface, central bulk, and invasive front, was extracted from formalin-fixed paraffin-embedded sections of colorectal cancer patients. The genome-wide methylation profiles were generated with methylation array. The most variable methylated probes were selected to construct a DNA methylation-based heterogeneity (MeHEG) estimation tool that can deconvolve the proportion of each reference tumor region with the support vector machine model-based method. A PCR-based assay for quantitative analysis of DNA methylation (QASM) was developed to specifically determine the methylation status of each CpG in MeHEG assay at single-base resolution to realize fast evaluation of epigenetic heterogeneity. Results In the discovery set with 79 patients, the differentially methylated CpGs among the three tumor regions were found. The 7 most representative CpGs were identified and subsequently selected to develop the MeHEG algorithm. We validated its performance of deconvolution of tumor regions in an independent cohort. In addition, we showed the significant association of MeHEG-based epigenetic heterogeneity with the genomic heterogeneity in mutation and copy number variation in our in-house and TCGA cohorts. Besides, we found that the patients with higher MeHEG score had worse disease-free and overall survival outcomes. Finally, we found dynamic change of epigenetic heterogeneity based on MeHEG score in cancer cells under the treatment of therapeutic drugs. Conclusion By developing a 7-loci panel using a machine learning approach combined with the QASM assay for PCR-based application, we present a valuable method for evaluating intratumoral heterogeneity. The MeHEG algorithm offers novel insights into tumor heterogeneity from an epigenetic perspective, potentially enriching current knowledge of tumor complexity and providing a new tool for clinical and research applications in cancer biology.

Abstract Stomach adenocarcinoma (STAD) is a prevalent malignancy that is highly aggressive and heterogeneous. Intratumor heterogeneity (ITH) showed strong link to tumor progression and metastasis. High ITH may promote tumor evolution. An ITH-related signature (IRS) was created using as integrative technique including 10 machine learning methods based on TCGA, GSE15459, GSE26253, GSE62254 and GSE84437 datasets. The relevance of IRS in predicting the advantages of immunotherapy was assessed using a number of prediction scores and three immunotherapy datasets (GSE78220, IMvigor210 and GSE91061). Vitro experiments were performed to verify the biological functions of AKR1B1. The RSF + Enet (alpha = 0.1) projected model was proposed as the ideal IRS because it had the highest average C-index. The IRS demonstrated a strong performance in serving as an independent risk factor for the clinical outcome of STAD patients. It performed exceptionally well in predicting the overall survival rate of STAD patients, as seen by the TCGA cohort’s AUC of 1-, 3-, and 5-year ROC curves, which were 0.689, 0.683, and 0.669, respectively. A low IRS score demonstrated a superior response to immunotherapy, as seen by a lower TIDE score, lower immune escape score, greater TMB score, higher PD1&CTLA4 immunophenoscore, higher response rate, and improved prognosis. Common chemotherapeutic and targeted treatment regimens had lower IC50 values in the group with higher IRS scores. Vitro experiment showed that AKR1B1 was upregulated in STAD and knockdown of AKR1B1 obviously suppressed tumor cell proliferation and migration. The present investigation produced the best IRS for STAD, which may be applied to prognostication, risk stratification, and therapy planning for STAD patients.

Neuroblastoma (NB) is the most common type of extracranial solid tumors in children. Despite the advancements in treatment strategies over the past years, the overall survival rate in patients within the high-risk NB group remains less than 50%. Therefore, new treatment options are urgently needed for this group of patients. Compared with genomic aberrations, proteomic alterations are more dynamic and complex, as well as more directly related to pathological phenotypes and external perturbations such as environmental changes and drug treatments. This review focuses on specific examples of proteomics application in various fundamental aspects of NB research, including tumorigenesis, drug treatment, drug resistance, and highlights potential protein signatures and related signaling pathways with translational values for clinical practice. Moreover, emerging cutting-edge proteomic techniques, such as single cell and spatial proteomics, as well as mass spectrometry imaging, are discussed for their potentials to probe intratumor heterogeneity of NB. [ABSTRACT FROM AUTHOR]

Stomach adenocarcinoma (STAD) is a prevalent malignancy that is highly aggressive and heterogeneous. Intratumor heterogeneity (ITH) showed strong link to tumor progression and metastasis. High ITH may promote tumor evolution. An ITH-related signature (IRS) was created using as integrative technique including 10 machine learning methods based on TCGA, GSE15459, GSE26253, GSE62254 and GSE84437 datasets. The relevance of IRS in predicting the advantages of immunotherapy was assessed using a number of prediction scores and three immunotherapy datasets (GSE78220, IMvigor210 and GSE91061). Vitro experiments were performed to verify the biological functions of AKR1B1. The RSF + Enet (alpha = 0.1) projected model was proposed as the ideal IRS because it had the highest average C-index. The IRS demonstrated a strong performance in serving as an independent risk factor for the clinical outcome of STAD patients. It performed exceptionally well in predicting the overall survival rate of STAD patients, as seen by the TCGA cohort's AUC of 1-, 3-, and 5-year ROC curves, which were 0.689, 0.683, and 0.669, respectively. A low IRS score demonstrated a superior response to immunotherapy, as seen by a lower TIDE score, lower immune escape score, greater TMB score, higher PD1&CTLA4 immunophenoscore, higher response rate, and improved prognosis. Common chemotherapeutic and targeted treatment regimens had lower IC50 values in the group with higher IRS scores. Vitro experiment showed that AKR1B1 was upregulated in STAD and knockdown of AKR1B1 obviously suppressed tumor cell proliferation and migration. The present investigation produced the best IRS for STAD, which may be applied to prognostication, risk stratification, and therapy planning for STAD patients. [ABSTRACT FROM AUTHOR]

To quantify intratumor heterogeneity (ITH) in clinical T1 stage lung adenocarcinoma presenting as pure ground-glass nodules (pGGN) on computed tomography, assessing its value in distinguishing histological subtypes. An ITH score was developed for quantitative measurement by integrating local radiomics features and global pixel distribution patterns. Diagnostic efficacy in distinguishing histological subtypes was evaluated using receiver operating characteristic curve analysis and area under the curve (AUC) values. The ITH score's performance was compared to those of conventional radiomics (C-radiomics), and radiological assessments conducted by experienced radiologists. The ITH score demonstrated excellent performance in distinguishing lepidic-predominant adenocarcinoma (LPA) from other histological subtypes of clinical T1 stage lung adenocarcinoma presenting as pGGN. It outperformed both C-radiomics and radiological findings, exhibiting higher AUCs of 0.784 (95% confidence interval [CI]: 0.742–0.826) and 0.801 (95% CI: 0.739–0.863) in the training and validation cohorts, respectively. The AUCs of C-radiomics were 0.764 (95% CI: 0.718–0.810, DeLong test, p = 0.025) and 0.760 (95% CI: 0.692–0.829, p = 0.023) and those of radiological findings were 0.722 (95% CI: 0.673–0.771, p = 0.003) and 0.754 (95% CI: 0.684–0.823, p = 0.016) in the training and validation cohorts, respectively. Subgroup analysis revealed varying diagnostic efficacy across clinical T1 stages, with the highest efficacy in the T1a stage, followed by the T1b stage, and lowest in the T1c stage. The ITH score presents a superior method for evaluating histological subtypes and distinguishing LPA from other subtypes in clinical T1 stage lung adenocarcinoma presenting as pGGN. [ABSTRACT FROM AUTHOR]

Featured Application: Quantitative characterization of intratumor heterogeneity using medical imaging is valuable for guiding theranostic technology in inductive moderate hyperthermia for sarcoma patients. Evaluating intratumor heterogeneity with image texture analysis offers a more sophisticated understanding of sarcoma response to treatment. We examined the effects of inductive moderate hyperthermia (IMH) on sarcoma-45 growth and intratumor heterogeneity across tissue, cellular and molecular levels using magnetic resonance imaging (MRI), ultrasound and histology image analysis. IMH (42 MHz, 20 W) inhibited sarcoma-45 growth kinetics by 34% compared to the untreated control group. T2-weighted MRI brightness was increased by 42%, reflecting more extensive tumor necrosis, while Young's modulus increased by 37% due to more pronounced connective tissue replacement in response to IMH. Whereas calculations of Moran's spatial autocorrelation index revealed distinctions in heterogeneity between tumor core, periphery and capsule regions of interest (ROIs) on MRI, ultrasound and histological examination in the untreated tumor-bearing animals, there was no significant difference between core and periphery after IMH. Exposure to IMH increased overall tumor ROI heterogeneity by 22% on MRI but reduced heterogeneity in the core and periphery on ultrasound and histology images. Ki-67 protein distribution was 25% less heterogeneous on the tumor periphery after IMH. Therefore, this study provides a quantitative characterization of IMH effects on different manifestations of intratumor sarcoma-45 heterogeneity using experimental imaging data. [ABSTRACT FROM AUTHOR]

Simple Summary: Human cells are typically diploid, that is, they contain two sets of chromosomes. Some cells, however, contain three or more sets of chromosomes and are called polyploid. In the early 2000s, Kirsten Walen and Rengaswami Rajaraman and his associates independently reported that polyploid human cells are capable of undergoing asymmetric division via nuclear budding and bursting (amitosis), giving rise to daughter cells that proliferate rapidly and can contribute to tumorigenesis (transformation of normal cells to a neoplastic state). This commentary provides an update on these intriguing discoveries. Cell division is crucial for the survival of living organisms. Human cells undergo three types of cell division: mitosis, meiosis, and amitosis. The former two types occur in somatic cells and germ cells, respectively. Amitosis involves nuclear budding and occurs in cells that exhibit abnormal nuclear morphology (e.g., polyploidy) with increased cell size. In the early 2000s, Kirsten Walen and Rengaswami Rajaraman and his associates independently reported that polyploid human cells are capable of producing progeny via amitotic cell division, and that a subset of emerging daughter cells proliferate rapidly, exhibit stem cell-like properties, and can contribute to tumorigenesis. Polyploid cells that arise in solid tumors/tumor-derived cell lines are referred to as polyploid giant cancer cells (PGCCs) and are known to contribute to therapy resistance and disease recurrence following anticancer treatment. This commentary provides an update on some of these intriguing discoveries as a tribute to Drs. Walen and Rajaraman. [ABSTRACT FROM AUTHOR]

Chronic infection of hepatitis B virus (HBV) is the major cause of hepatocellular carcinoma (HCC). Notably, 90% of HBV-positive HCC cases exhibit detectable HBV integrations, hinting at the potential early entanglement of these viral integrations in tumorigenesis and their subsequent oncogenic implications. Nevertheless, the precise chronology of integration events during HCC tumorigenesis, alongside their sequential structural patterns, has remained elusive thus far. In this study, we applied whole-genome sequencing to multiple biopsies extracted from six HBV-positive HCC cases. Through this approach, we identified point mutations and viral integrations, offering a blueprint for the intricate tumor phylogeny of these samples. The emergent narrative paints a rich tapestry of diverse evolutionary trajectories characterizing the analyzed tumors. We uncovered oncogenic integration events in some samples that appear to happen before and during the initiation stage of tumor development based on their locations in reconstituted trajectories. Furthermore, we conducted additional long-read sequencing of selected samples and unveiled integration-bridged chromosome rearrangements and tandem repeats of the HBV sequence within integrations. In summary, this study revealed premalignant oncogenic and sequential complex integrations and highlighted the contributions of HBV integrations to HCC development and genome instability.

IntroductionOsteosarcoma (OS) is a malignancy of the bone that mainly afflicts younger individuals. Despite existing treatment approaches, patients with metastatic or recurrent disease generally face poor prognoses. A greater understanding of the tumor microenvironment (TME) is critical for enhancing outcomes in OS patients.MethodsThe clinical and RNA expression data of OS patients were extracted from the TARGET database. The single-cell RNA sequencing (scRNA-seq) data of 11 OS samples was retrieved from the GEO database, and analyzed using the Seurat package of R software. Copy number variation (CNV) was analyzed using the InferCNV software. The potential interactions between the different cells in the TME was analyzed with the CellChat package. A multi-algorithm-based computing framework was used to calculate the tumor-infiltrating immune cell (TIIC) scores. A prognostic model was constructed using 20 machine learning algorithms. Maftools R package was used to characterize the genomic variation landscapes in the patient groups stratified by TIIC score. The human OS cell lines MG63 and U2OS were used for the functional assays. Cell proliferation and migration were analyzed by the EdU assay and Transwell assay respectively. CLK1 protein expression was measured by immunoblotting.ResultsWe observed higher CNV in the OS cells compared to endothelial cells. In addition, there was distinct transcriptional heterogeneity across the OS cells, and cluster 1 was identified as the terminal differentiation state. S100A1, TMSB4X, and SLPI were the three most significantly altered genes along with the pseudo-time trajectory. Cell communication analysis revealed an intricate network between S100A1+ tumor cells and other TME cells. Cluster 1 exhibited significantly higher aggressiveness features, which correlated with worse clinical outcomes. A prognostic model was developed based on TIIC-related genes that were screened using machine learning algorithms, and validated in multiple datasets. Higher TIIC signature score was associated with lower cytotoxic immune cell infiltration and generally inferior immune response and survival rate. Moreover, TIIC signature score was further validated in the datasets of other cancers. CLK1 was identified as a potential oncogene that promotes the proliferation and migration OS cells.ConclusionA TIIC-based gene signature was developed that effectively predicted the prognosis of OS patients, and was significantly associated with immune infiltration and immune response. Moreover, CLK1 was identified as an oncogene and potential therapeutic target for OS.

Abstract Introduction Hepatocellular carcinoma (HCC) is the most common form of liver cancer globally and remains a major cause of cancer-related deaths. HCC exhibits significant intra-tumoral and interpatient heterogeneity, impacting treatment efficacy and patient prognosis. Methods We acquired transcriptome data from the TCGA and ICGC databases, as well as liver cancer chip data from the GEO database, and processed the data for subsequent analysis. We also obtained single cell data from the GEO database and performed data analysis using the Seurat package. To further investigate epithelial cell subgroups and their copy number variations, we used the Seurat workflow for subgroup classification and the InferCNV software for CNV analysis, utilizing endothelial cells as a reference. Pseudo-time analysis and transcription factor analysis of epithelial cells were performed using the monocle2 and SCENIC software, respectively. To assess intercellular communication, we employed the CellChat package to identify potential ligand-receptor interactions. We also analyzed gene expression differences and conducted enrichment analysis using the limma and clusterProfiler packages. Additionally, we established tumor-related risk characteristics using Cox analysis and Lasso regression, and predicted immunotherapy response using various datasets. Results The samples were classified into 23 clusters, with malignant epithelial cells being the majority. Trajectory analysis revealed the differentiation states of the malignant epithelial cells, with cluster 1 being in the terminal state. Functional analysis revealed higher aggressiveness and epithelial-mesenchymal transition (EMT) scores in cluster 1, indicating a higher propensity for metastasis. RBP4+ tumor cells were highly enriched with hypoxia process and intensive cell-to-cell communication. A prognostic model was established, and immune infiltration analysis showed increased infiltration in the high-risk group. TP53 demonstrated significant differences in mutation rate between the two risk groups. Validation analysis confirmed the up-regulation of model genes, including AKR1B10, ARL6IP4, ATP6V0B, and BSG in tumor tissues. Conclusion A prognostic model was established based on HCC malignant cell associated gene signature, displaying decent prognosis guiding effectiveness in the multiple cohorts. The study provided comprehensive insights into the heterogeneity and potential therapeutic targets of LIHC.

Biofabrication techniques enable the performance of bioinspired three‐dimensional (3D) matrices resembling primary tumors. To validate their reliability, embedded cells may express complex biophysical responses. Among others, the emergence of tumor heterogeneity and the generation of Polyploid Giant Cancer Cells (PGCC), as a result of the mechanical stress, are two of the most challenging hallmarks to resemble in vitro. Here, these phenomena are studied in cells cultured on two‐dimensional (2D) flasks, in 3D spheroids, or immobilized within 3D polymer‐based tumor‐like microcapsules. These results show that cells cultured in 3D microcapsules exhibited an enhanced biomechanical heterogeneity, a higher number of PGCC, and an increased exertion of cell‐matrix attachment forces with respect to the other two experimental conditions. Additionally, cells isolated from tumor‐like microcapsules redistribute and align the cytoplasmatic protein Caveolin‐1, and upregulate markers involved in cell proliferation (i.e., Ki67), metastasis (i.e., TGF‐β1, TGF‐β‐R2), and epithelial to mesenchymal transition, to name a few. These hallmarks are barely described in the past as a result of the confinement and mechanical stress. Thus, in this work it is demonstrated that both the mechanical stress and confinement are required to stimulate cell polyploidy and biomechanical heterogeneity, which can be easily addressed by immobilizing breast cancer cells in tumor‐like microcapsules. [ABSTRACT FROM AUTHOR]

Glioblastoma cell lines derived from different patients are widely used in tumor biology research and drug screening. A key feature of glioblastoma is the high level of inter- and intratumor heterogeneity that accounts for treatment resistance. Our aim was to investigate whether intratumor heterogeneity is maintained in cell models. Single-cell RNA sequencing was used to investigate the cellular composition of a tumor sample and six patient-derived glioblastoma cell lines. Three cell lines preserved the mutational profile of the original tumor, whereas three others differed from their precursors. Copy-number variation analysis showed significantly rearranged genomes in all the cell lines and in the tumor sample. The tumor had the most complex cell composition, including cancer cells and microenvironmental cells. Cell lines with a conserved genome had less diverse cellularity, and during cultivation, a relative increase in the stem-cell-derived progenitors was noticed. Cell lines with genomes different from those of the primary tumors mainly contained neural progenitor cells and microenvironmental cells. The establishment of cell lines without the driver mutations that are intrinsic to the original tumors may be related to the selection of clones or cell populations during cultivation. Thus, patient-derived glioblastoma cell lines differ substantially in their cellular profile, which should be taken into account in translational studies. [ABSTRACT FROM AUTHOR]

Simple Summary: This study investigates the role of visual intratumor heterogeneity (ITH) in breast cancer progression. By analyzing histologic images from the Carolina Breast Cancer Study (CBCS) and the Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) data using advanced image processing and machine learning techniques, we developed a measure of tumor heterogeneity based on visual features. Our findings indicate that tumors with low visual heterogeneity exhibited a higher risk of recurrence and were more likely to come from patients whose tumors comprised of only one subclone or had a TP53 mutation. Conversely, high visual heterogeneity was correlated with a more favorable prognosis. These results suggest that visual heterogeneity provides complementary information to molecular markers. A comprehensive understanding of both the visual and molecular aspects of heterogeneity has the potential to offer novel insights for treatment strategies. High intratumoral heterogeneity is thought to be a poor prognostic indicator. However, the source of heterogeneity may also be important, as genomic heterogeneity is not always reflected in histologic or 'visual' heterogeneity. We aimed to develop a predictor of histologic heterogeneity and evaluate its association with outcomes and molecular heterogeneity. We used VGG16 to train an image classifier to identify unique, patient-specific visual features in 1655 breast tumors (5907 core images) from the Carolina Breast Cancer Study (CBCS). Extracted features for images, as well as the epithelial and stromal image components, were hierarchically clustered, and visual heterogeneity was defined as a greater distance between images from the same patient. We assessed the association between visual heterogeneity, clinical features, and DNA-based molecular heterogeneity using generalized linear models, and we used Cox models to estimate the association between visual heterogeneity and tumor recurrence. Basal-like and ER-negative tumors were more likely to have low visual heterogeneity, as were the tumors from younger and Black women. Less heterogeneous tumors had a higher risk of recurrence (hazard ratio = 1.62, 95% confidence interval = 1.22–2.16), and were more likely to come from patients whose tumors were comprised of only one subclone or had a TP53 mutation. Associations were similar regardless of whether the image was based on stroma, epithelium, or both. Histologic heterogeneity adds complementary information to commonly used molecular indicators, with low heterogeneity predicting worse outcomes. Future work integrating multiple sources of heterogeneity may provide a more comprehensive understanding of tumor progression. [ABSTRACT FROM AUTHOR]

Intratumor heterogeneity (ITH) of bladder cancer (BLCA) contributes to therapy resistance and immune evasion affecting clinical prognosis. The molecular and cellular mechanisms contributing to BLCA ITH generation remain elusive. It is found that a TM4SF1‐positive cancer subpopulation (TPCS) can generate ITH in BLCA, evidenced by integrative single cell atlas analysis. Extensive profiling of the epigenome and transcriptome of all stages of BLCA revealed their evolutionary trajectories. Distinct ancestor cells gave rise to low‐grade noninvasive and high‐grade invasive BLCA. Epigenome reprograming led to transcriptional heterogeneity in BLCA. During early oncogenesis, epithelial‐to‐mesenchymal transition generated TPCS. TPCS has stem‐cell‐like properties and exhibited transcriptional plasticity, priming the development of transcriptionally heterogeneous descendent cell lineages. Moreover, TPCS prevalence in tumor is associated with advanced stage cancer and poor prognosis. The results of this study suggested that bladder cancer interacts with its environment by acquiring a stem cell‐like epigenomic landscape, which might generate ITH without additional genetic diversification. [ABSTRACT FROM AUTHOR]

Introduction: Hepatocellular carcinoma (HCC) is the most common form of liver cancer globally and remains a major cause of cancer-related deaths. HCC exhibits significant intra-tumoral and interpatient heterogeneity, impacting treatment efficacy and patient prognosis. Methods: We acquired transcriptome data from the TCGA and ICGC databases, as well as liver cancer chip data from the GEO database, and processed the data for subsequent analysis. We also obtained single cell data from the GEO database and performed data analysis using the Seurat package. To further investigate epithelial cell subgroups and their copy number variations, we used the Seurat workflow for subgroup classification and the InferCNV software for CNV analysis, utilizing endothelial cells as a reference. Pseudo-time analysis and transcription factor analysis of epithelial cells were performed using the monocle2 and SCENIC software, respectively. To assess intercellular communication, we employed the CellChat package to identify potential ligand-receptor interactions. We also analyzed gene expression differences and conducted enrichment analysis using the limma and clusterProfiler packages. Additionally, we established tumor-related risk characteristics using Cox analysis and Lasso regression, and predicted immunotherapy response using various datasets. Results: The samples were classified into 23 clusters, with malignant epithelial cells being the majority. Trajectory analysis revealed the differentiation states of the malignant epithelial cells, with cluster 1 being in the terminal state. Functional analysis revealed higher aggressiveness and epithelial-mesenchymal transition (EMT) scores in cluster 1, indicating a higher propensity for metastasis. RBP4+ tumor cells were highly enriched with hypoxia process and intensive cell-to-cell communication. A prognostic model was established, and immune infiltration analysis showed increased infiltration in the high-risk group. TP53 demonstrated significant differences in mutation rate between the two risk groups. Validation analysis confirmed the up-regulation of model genes, including AKR1B10, ARL6IP4, ATP6V0B, and BSG in tumor tissues. Conclusion: A prognostic model was established based on HCC malignant cell associated gene signature, displaying decent prognosis guiding effectiveness in the multiple cohorts. The study provided comprehensive insights into the heterogeneity and potential therapeutic targets of LIHC. [ABSTRACT FROM AUTHOR]

Tumors consist of cancer cells with different genetic, epigenetic, and phenotypic properties. Cancer stem cells are an important subpopulation of heterogeneous cancer cells and are capable of initiating and propagating tumors. The term cancer stem cells has become broader in efforts to understand their phenotypic plasticity to switch fates between self-renewal and differentiation. Cancer stem cell plasticity is significantly associated with the initiation of metastasis, resistance to therapy, and tumor recurrence. With our broadened knowledge of epigenetic regulation and metabolic reprogramming as key elements enabling such capabilities, an expansive body of literature has demonstrated the functional importance of each element in contributing to cancer stem cell characteristics. Recently, the direct interplay between epigenetic regulation and metabolic reprogramming has begun to be appreciated in the context of cancer stem cells with growing interest. In this review, we discuss the mechanisms by which cancer stem cells orchestrate the reciprocal regulation of cellular metabolism and epigenetic alterations. In the discussion, compelling, unanswered questions on this topic have been elaborated for the interest of the research community and how recent technological developments help tackle such research ideas. A comprehensive understanding of cancer stem cell attributes that are largely governed by epigenetic and metabolic reprogramming would enable the advancement of precise therapeutic options and the prediction of better responses to drugs, holding great promise in cancer treatment and cure.

Abstract Background Circulating tumor cells (CTCs) hold immense promise for unraveling tumor heterogeneity and understanding treatment resistance. However, conventional methods, especially in cancers like non-small cell lung cancer (NSCLC), often yield low CTC numbers, hindering comprehensive analyses. This study addresses this limitation by employing diagnostic leukapheresis (DLA) to cancer patients, enabling the screening of larger blood volumes. To leverage DLA’s full potential, this study introduces a novel approach for CTC enrichment from DLAs. Methods DLA was applied to six advanced stage NSCLC patients. For an unbiased CTC enrichment, a two-step approach based on negative depletion of hematopoietic cells was used. Single-cell (sc) whole-transcriptome sequencing was performed, and CTCs were identified based on gene signatures and inferred copy number variations. Results Remarkably, this innovative approach led to the identification of unprecedented 3,363 CTC transcriptomes. The extensive heterogeneity among CTCs was unveiled, highlighting distinct phenotypes related to the epithelial-mesenchymal transition (EMT) axis, stemness, immune responsiveness, and metabolism. Comparison with sc transcriptomes from primary NSCLC cells revealed that CTCs encapsulate the heterogeneity of their primary counterparts while maintaining unique CTC-specific phenotypes. Conclusions In conclusion, this study pioneers a transformative method for enriching CTCs from DLA, resulting in a substantial increase in CTC numbers. This allowed the creation of the first-ever single-cell whole transcriptome in-depth characterization of the heterogeneity of over 3,300 NSCLC-CTCs. The findings not only confirm the diagnostic value of CTCs in monitoring tumor heterogeneity but also propose a CTC-specific signature that can be exploited for targeted CTC-directed therapies in the future. This comprehensive approach signifies a major leap forward, positioning CTCs as a key player in advancing our understanding of cancer dynamics and paving the way for tailored therapeutic interventions.

The many limitations of implementing anticancer strategies under the term “precision oncology” have been extensively discussed. While some authors propose promising future directions, others are less optimistic and use phrases such as illusion, hype, and false hypotheses. The reality is revealed by practicing clinicians and cancer patients in various online publications, one of which has stated that “in the quest for the next cancer cure, few researchers bother to look back at the graveyard of failed medicines to figure out what went wrong”. The message is clear: Novel therapeutic strategies with catchy names (e.g., synthetic “lethality”) have not fulfilled their promises despite decades of extensive research and clinical trials. The main purpose of this review is to discuss key challenges in solid tumor therapy that surprisingly continue to be overlooked by the Nomenclature Committee on Cell Death (NCCD) and numerous other authors. These challenges include: The impact of chemotherapy-induced genome chaos (e.g., multinucleation) on resistance and relapse, oncogenic function of caspase 3, cancer cell anastasis (recovery from late stages of apoptosis), and pitfalls of ubiquitously used preclinical chemosensitivity assays (e.g., cell “viability” and tumor growth delay studies in live animals) that score such pro-survival responses as “lethal” events. The studies outlined herein underscore the need for new directions in the management of solid tumors.

Background: Circulating tumor cells (CTCs) hold immense promise for unraveling tumor heterogeneity and understanding treatment resistance. However, conventional methods, especially in cancers like non-small cell lung cancer (NSCLC), often yield low CTC numbers, hindering comprehensive analyses. This study addresses this limitation by employing diagnostic leukapheresis (DLA) to cancer patients, enabling the screening of larger blood volumes. To leverage DLA's full potential, this study introduces a novel approach for CTC enrichment from DLAs. Methods: DLA was applied to six advanced stage NSCLC patients. For an unbiased CTC enrichment, a two-step approach based on negative depletion of hematopoietic cells was used. Single-cell (sc) whole-transcriptome sequencing was performed, and CTCs were identified based on gene signatures and inferred copy number variations. Results: Remarkably, this innovative approach led to the identification of unprecedented 3,363 CTC transcriptomes. The extensive heterogeneity among CTCs was unveiled, highlighting distinct phenotypes related to the epithelial-mesenchymal transition (EMT) axis, stemness, immune responsiveness, and metabolism. Comparison with sc transcriptomes from primary NSCLC cells revealed that CTCs encapsulate the heterogeneity of their primary counterparts while maintaining unique CTC-specific phenotypes. Conclusions: In conclusion, this study pioneers a transformative method for enriching CTCs from DLA, resulting in a substantial increase in CTC numbers. This allowed the creation of the first-ever single-cell whole transcriptome in-depth characterization of the heterogeneity of over 3,300 NSCLC-CTCs. The findings not only confirm the diagnostic value of CTCs in monitoring tumor heterogeneity but also propose a CTC-specific signature that can be exploited for targeted CTC-directed therapies in the future. This comprehensive approach signifies a major leap forward, positioning CTCs as a key player in advancing our understanding of cancer dynamics and paving the way for tailored therapeutic interventions. [ABSTRACT FROM AUTHOR]

Simple Summary: For nearly half a century, a mainstay and goal of medical oncology has been to identify novel anticancer drugs and therapeutic strategies to promote the effective elimination of cancer cells via apoptosis. In the past decade, however, single cell biology has revealed that apoptosis is not obligatorily a permanent cell fate. The purpose of this commentary is to briefly discuss laboratory and clinical studies that have revealed the dark side of apoptosis in treating patients with solid tumors. Most therapeutic strategies for solid tumor malignancies are designed based on the hypothesis that cancer cells evade apoptosis to exhibit therapy resistance. This is somewhat surprising given that clinical studies published since the 1990s have demonstrated that increased apoptosis in solid tumors is associated with cancer aggressiveness and poor clinical outcome. This is consistent with more recent reports demonstrating non-canonical (pro-survival) roles for apoptotic caspases, including caspase 3, as well as the ability of cancer cells to recover from late stages of apoptosis via a process called anastasis. These activities are essential for the normal development and maintenance of a healthy organism, but they also enable malignant cells (including cancer stem cells) to resist anticancer treatment and potentially contribute to clinical dormancy (minimal residual disease). Like apoptosis, therapy-induced cancer cell dormancy (durable proliferation arrest reflecting various manifestations of genome chaos) is also not obligatorily a permanent cell fate. However, as briefly discussed herein, compelling pre-clinical studies suggest that (reversible) dormancy might be the "lesser evil" compared to treacherous apoptosis. [ABSTRACT FROM AUTHOR]

Background/Aim: A genomic analysis based on next-generation sequencing is important for deciding cancer treatment strategies. Cancer tissue sometimes displays intratumor heterogeneity and a pathologic specimen may contain more than two tumor grades. Although tumor grades are very important for the cancer prognosis, the impact of higher tumor grade distribution in a specimen used for a genomic analysis is unknown. Patients and Methods: We retrospectively analyzed the data of 61 clear cell carcinoma and 46 prostate cancer patients that were diagnosed between December 2018 and August 2022 using the GeneRead Human Comprehensive Cancer Panel or SureSelect PrePool custom Tier2. Genome annotation and curation were performed using the GenomeJack software. Results: Tumor mutation burden (TMB) was increased in proportion to the higher tumor grade distribution in grade 2 clear cell renal cell carcinoma (ccRCC). In PC, Grade Group 3/4 specimens that included an increased distribution of Gleason pattern 4 had more frequent gene mutations. Conclusion: Our results suggest the importance of selecting the maximum distribution of higher tumor grade areas to obtain results on the precise gene alterations for genomics-focused treatments. [ABSTRACT FROM AUTHOR]

Abstract Objectives Intratumor heterogeneity (ITH) is an important factor for clinical outcomes in patients with multiple myeloma (MM). High ITH has been proven to be a key reason for tumor immune escape and treatment resistance. Neoantigens are thought to be associated with ITH, but the specific correlation and functional basis for this remains unclear. Methods We study this question through the whole‐exome sequencing (WES) data from 43 high ITH newly diagnosed MM patients in our center. Mutant allele tumor heterogeneity (MATH) was conducted to quantify ITH. The cutoff value for high intratumor heterogeneity was determined by comparing MATH of different kinds of tumors. NeoPredPipe was performed to predict neoantigens and binding affinity. Results Compared to other tumors, MM has a relatively low tumor mutation burden but a high ITH. Patients with high MATH had significantly shorter progression‐free survival times than those with low MATH (p = 0.001). In high ITH samples, there is a decrease in strong‐binding neoantigens (p = 0.019). The loss of strong‐binding neoantigens is a key factor for insensitivity to therapy (p = 0.015). Loss of heterozygosity in HLA was not observed. In addition, patients with fewer neoantigens loss had higher rates of disease remission (p = 0.047). CD8 + T cells (p = 0.012) and NK cells (p = 0.011) decreased significantly in patients with high neoantigens loss rate. A prediction model based on neoantigens was built to evaluate the strength of immune escape. Conclusion The loss of strong‐binding neoantigens explains why tumors with high ITH have a higher degree of immune escape and may be feasible for deciding the clinical treatment of MM.

Neuroblastoma (NB) is the most common type of extracranial solid tumors in children. Despite the advancements in treatment strategies over the past years, the overall survival rate in patients within the high-risk NB group remains less than 50%. Therefore, new treatment options are urgently needed for this group of patients. Compared with genomic aberrations, proteomic alterations are more dynamic and complex, as well as more directly related to pathological phenotypes and external perturbations such as environmental changes and drug treatments. This review focuses on specific examples of proteomics application in various fundamental aspects of NB research, including tumorigenesis, drug treatment, drug resistance, and highlights potential protein signatures and related signaling pathways with translational values for clinical practice. Moreover, emerging cutting-edge proteomic techniques, such as single cell and spatial proteomics, as well as mass spectrometry imaging, are discussed for their potentials to probe intratumor heterogeneity of NB.

Evaluating intratumor heterogeneity with image texture analysis offers a more sophisticated understanding of sarcoma response to treatment. We examined the effects of inductive moderate hyperthermia (IMH) on sarcoma-45 growth and intratumor heterogeneity across tissue, cellular and molecular levels using magnetic resonance imaging (MRI), ultrasound and histology image analysis. IMH (42 MHz, 20 W) inhibited sarcoma-45 growth kinetics by 34% compared to the untreated control group. T2-weighted MRI brightness was increased by 42%, reflecting more extensive tumor necrosis, while Young’s modulus increased by 37% due to more pronounced connective tissue replacement in response to IMH. Whereas calculations of Moran’s spatial autocorrelation index revealed distinctions in heterogeneity between tumor core, periphery and capsule regions of interest (ROIs) on MRI, ultrasound and histological examination in the untreated tumor-bearing animals, there was no significant difference between core and periphery after IMH. Exposure to IMH increased overall tumor ROI heterogeneity by 22% on MRI but reduced heterogeneity in the core and periphery on ultrasound and histology images. Ki-67 protein distribution was 25% less heterogeneous on the tumor periphery after IMH. Therefore, this study provides a quantitative characterization of IMH effects on different manifestations of intratumor sarcoma-45 heterogeneity using experimental imaging data.

Abstract Background High oncogene expression in cancer cells is a major cause of rapid tumor progression and drug resistance. Recent cancer genome research has shown that oncogenes as well as regulatory elements can be amplified in the form of extrachromosomal DNA (ecDNA) or subsequently integrated into chromosomes as homogeneously staining regions (HSRs). These genome-level variants lead to the overexpression of the corresponding oncogenes, resulting in poor prognosis. Most existing detection methods identify ecDNA using whole genome sequencing (WGS) data. However, these techniques usually detect many false positive regions owing to chromosomal DNA interference. Results In the present study, an algorithm called “ATACAmp” that can identify ecDNA/HSRs in tumor genomes using ATAC-seq data has been described. High chromatin accessibility, one of the characteristics of ecDNA, makes ATAC-seq naturally enriched in ecDNA and reduces chromosomal DNA interference. The algorithm was validated using ATAC-seq data from cell lines that have been experimentally determined to contain ecDNA regions. ATACAmp accurately identified the majority of validated ecDNA regions. AmpliconArchitect, the widely used ecDNA detecting tool, was used to detect ecDNA regions based on the WGS data of the same cell lines. Additionally, the Circle-finder software, another tool that utilizes ATAC-seq data, was assessed. The results showed that ATACAmp exhibited higher accuracy than AmpliconArchitect and Circle-finder. Moreover, ATACAmp supported the analysis of single-cell ATAC-seq data, which linked ecDNA to specific cells. Conclusions ATACAmp, written in Python, is freely available on GitHub under the MIT license: https://github.com/chsmiss/ATAC-amp . Using ATAC-seq data, ATACAmp offers a novel analytical approach that is distinct from the conventional use of WGS data. Thus, this method has the potential to reduce the cost and technical complexity associated ecDNA analysis.

Abstract Background Patients with epithelial ovarian carcinoma (EOC) are usually diagnosed at an advanced stage with tumour cell invasion. However, identifying the underlying molecular mechanisms and biomarkers of EOC proliferation and invasion remains challenging. Results Herein, we explored the relationship between tumour microenvironment (TME) reprogramming and tissue invasion based on single-cell RNA sequencing (scRNA-seq) datasets. Interestingly, hypoxia, oxidative phosphorylation (OXPHOS) and glycolysis, which have biologically active trajectories during epithelial mesenchymal transition (EMT), were positively correlated. Moreover, energy metabolism and anti-apoptotic activity were found to be critical contributors to intratumor heterogeneity. In addition, HMGA1, EGR1 and RUNX1 were found to be critical drivers of the EMT process in EOC. Experimental validation revealed that suppressing EGR1 expression inhibited tumour cell invasion, significantly upregulated the expression of E-cadherin and decreased the expression of N-cadherin. In cell components analysis, cancer-associated fibroblasts (CAFs) were found to significantly contribute to immune infiltration and tumour invasion, and the accumulation of CAFs was associated with poorer patient survival. Conclusion We revealed the molecular mechanism and biomarkers of tumour invasion and TME reprogramming in EOC, which provides effective targets for the suppression of tumour invasion.

Background: Cholangiocarcinoma is a kind of epithelial cell malignancy with high mortality. Intratumor heterogeneity (ITH) is involved in tumor progression, aggressiveness, treatment resistance, and disease recurrence. Methods: Integrative machine learning procedure including 10 methods (random survival forest, elastic network, Lasso, Ridge, stepwise Cox, CoxBoost, partial least squares regression for Cox, supervised principal components, generalized boosted regression modeling, and survival support vector machine) was performed to construct an ITH-related signature (IRS) for cholangiocarcinoma. Single cell analysis was performed to clarify the communication between immune cell subtypes. Cellular experiment was used to verify the biological function of hub gene. Results: The optimal prognostic IRS developed by Lasso method served as an independent risk factor and had a stable and powerful performance in predicting the overall survival rate in cholangiocarcinoma, with the AUC of 2-, 3-, and 4-year ROC curve being 0.955, 0.950 and 1.000 in TCGA cohort. low IRS score indicated with a lower tumor immune dysfunction and exclusion score, lower tumor microsatellite instability, lower immune escape score, lower MATH score, and higher mutation burden score in cholangiocarcinoma. Single cell analysis revealed a strong communication between fibroblasts, microphage and epithelial cells by specific ligand-receptor pairs, including COL4A1-(ITGAV+ITGB8) and COL1A2-(ITGAV+ITGB8). Down-regulation of BET1L inhibited the proliferation, migration and invasion as well as promoted apoptosis of cholangiocarcinoma cell. Conclusion: Integrative machine learning analysis was performed to construct a novel IRS in cholangiocarcinoma. This IRS acted as an indicator for predicting the prognosis and immunotherapy benefits of cholangiocarcinoma patients.

Simple Summary: Clear cell renal cell carcinomas (CCRCCs) evolve as dynamic communities of individuals (cells) that are amenable to being studied under sociological rules. Here, the early period of development in CCRCC, progressing from initial homogeneity to high intratumor heterogeneity (ITH) and secondary clonal and sub-clonal diversification, is considered using the hawk-dove game. Fitness is a measure of biological aggressiveness in tumors. The results demonstrate that the fittest clone of a neoplasm in a heterogeneous context is fitter than the clone in a homogeneous environment in the early phases of tumor evolution. This study notes the advantages of a translational multidisciplinary approach in cancer research. Clear cell renal cell carcinoma (CCRCC) is an aggressive form of cancer and a paradigmatic example of intratumor heterogeneity (ITH). The hawk-dove game is a mathematical tool designed to analyze competition in biological systems. Using this game, the study reported here analyzes the early phase of CCRCC development, comparing clonal fitness in homogeneous (linear evolutionary) and highly heterogeneous (branching evolutionary) models. Fitness in the analysis is a measure of tumor aggressiveness. The results show that the fittest clone in a heterogeneous environment is fitter than the clone in a homogeneous context in the early phases of tumor evolution. Early and late periods of tumor evolution in CCRCC are also compared. The study shows the convergence of mathematical, histological, and genomics studies with respect to clonal aggressiveness in different periods of the natural history of CCRCC. Such convergence highlights the importance of multidisciplinary approaches for obtaining a better understanding of the intricacies of cancer. [ABSTRACT FROM AUTHOR]

Objectives: Intratumor heterogeneity (ITH) is an important factor for clinical outcomes in patients with multiple myeloma (MM). High ITH has been proven to be a key reason for tumor immune escape and treatment resistance. Neoantigens are thought to be associated with ITH, but the specific correlation and functional basis for this remains unclear. Methods: We study this question through the whole‐exome sequencing (WES) data from 43 high ITH newly diagnosed MM patients in our center. Mutant allele tumor heterogeneity (MATH) was conducted to quantify ITH. The cutoff value for high intratumor heterogeneity was determined by comparing MATH of different kinds of tumors. NeoPredPipe was performed to predict neoantigens and binding affinity. Results: Compared to other tumors, MM has a relatively low tumor mutation burden but a high ITH. Patients with high MATH had significantly shorter progression‐free survival times than those with low MATH (p = 0.001). In high ITH samples, there is a decrease in strong‐binding neoantigens (p = 0.019). The loss of strong‐binding neoantigens is a key factor for insensitivity to therapy (p = 0.015). Loss of heterozygosity in HLA was not observed. In addition, patients with fewer neoantigens loss had higher rates of disease remission (p = 0.047). CD8 + T cells (p = 0.012) and NK cells (p = 0.011) decreased significantly in patients with high neoantigens loss rate. A prediction model based on neoantigens was built to evaluate the strength of immune escape. Conclusion: The loss of strong‐binding neoantigens explains why tumors with high ITH have a higher degree of immune escape and may be feasible for deciding the clinical treatment of MM. [ABSTRACT FROM AUTHOR]

Abstract In this study, we investigated the association between PD‐L1 expression in tumor cells and underlying genetic mutations, which was analyzed in detail using laser microdissection and next‐generation sequencing analysis. To investigate whether driver mutations are involved in the background of PD‐L1 expression, the EGFR major activating mutation was selected as the most frequent driver mutation. Surgical resection specimens were used to extract sufficient amounts of nucleic acids for analysis, and the high tumor proportion score (TPS:100%) and low (TPS: 0%) PD‐L1‐expressing parts of the tumor were each laser microdissected to examine the association between PD‐L1 expression heterogeneity and genetic mutations within the same tumor. The association between PD‐L1 heterogeneity and gene mutations within the same tumor was investigated. Analysis showed no association between PD‐L1 expression heterogeneity and genetic variants, which were found to be almost identical. However, PD‐L1 expression was found to be associated with the number of tumor infiltrating lymphocytes (TILs) present in the tumor, which may be related to whether or not lymphocytes can infiltrate into the tumor depending on the tumor histological type (solid pattern, lepidic pattern, etc.) and other factors.

The molecular landscape and the intratumor heterogeneity (ITH) architecture of gastric linitis plastica (LP) are poorly understood. We performed whole‐exome sequencing (WES) and T‐cell receptor (TCR) sequencing on 40 tumor regions from four LP patients. The landscape and ITH at the genomic and immunological levels in LP tumors were compared with multiple cancers that have previously been reported. The lymphocyte infiltration was further assessed by immunohistochemistry (IHC) in LP tumors. In total, we identified 6339 non‐silent mutations from multi‐samples, with a median tumor mutation burden (TMB) of 3.30 mutations per Mb, comparable to gastric adenocarcinoma from the Cancer Genome Atlas (TCGA) cohort (P = 0.53). An extremely high level of genomic ITH was observed, with only 12.42%, 5.37%, 5.35%, and 30.67% of mutations detectable across 10 regions within the same tumors of each patient, respectively. TCR sequencing revealed that TCR clonality was substantially lower in LP than in multi‐cancers. IHC using antibodies against CD4, CD8, and PD‐L1 demonstrated scant T‐cell infiltration in the four LP tumors. Furthermore, profound TCR ITH was observed in all LP tumors, with no T‐cell clones shared across tumor regions in any of the patients, while over 94% of T‐cell clones were restricted to individual tumor regions. The Morisita overlap index (MOI) ranged from 0.21 to 0.66 among multi‐regions within the same tumors, significantly lower than that of lung cancer (P = 0.002). Our results show that LP harbored extremely high genomic and TCR ITH and suppressed T‐cell infiltration, suggesting a potential contribution to the frequent recurrence and poor therapeutic response of this adenocarcinoma.

Abstract Background Intratumor heterogeneity is a well-established hallmark of cancer that impedes cancer research, diagnosis, and treatment. Previously, we phenotypically sorted human breast cancer cells based on migratory potential. When injected into mice, highly migratory cells were weakly metastatic and weakly migratory cells were highly metastatic. The purpose of this study was to determine whether these weakly and highly migratory cells interact with each other in vitro or in vivo. Methods To assess the relationship between heterogeneity in cancer cell migration and metastatic fitness, MDA-MB-231 and SUM159PT triple negative breast cancer cells were phenotypically sorted into highly migratory and weakly migratory subpopulations and assayed separately and in a 1:1 mixture in vitro and in vivo for metastatic behaviors. Unpaired, two-tailed Student’s t-tests, Mann–Whitney tests, ordinary, one-way ANOVAs, and Kruskal–Wallis H tests were performed as appropriate with p

Background: High oncogene expression in cancer cells is a major cause of rapid tumor progression and drug resistance. Recent cancer genome research has shown that oncogenes as well as regulatory elements can be amplified in the form of extrachromosomal DNA (ecDNA) or subsequently integrated into chromosomes as homogeneously staining regions (HSRs). These genome-level variants lead to the overexpression of the corresponding oncogenes, resulting in poor prognosis. Most existing detection methods identify ecDNA using whole genome sequencing (WGS) data. However, these techniques usually detect many false positive regions owing to chromosomal DNA interference. Results: In the present study, an algorithm called "ATACAmp" that can identify ecDNA/HSRs in tumor genomes using ATAC-seq data has been described. High chromatin accessibility, one of the characteristics of ecDNA, makes ATAC-seq naturally enriched in ecDNA and reduces chromosomal DNA interference. The algorithm was validated using ATAC-seq data from cell lines that have been experimentally determined to contain ecDNA regions. ATACAmp accurately identified the majority of validated ecDNA regions. AmpliconArchitect, the widely used ecDNA detecting tool, was used to detect ecDNA regions based on the WGS data of the same cell lines. Additionally, the Circle-finder software, another tool that utilizes ATAC-seq data, was assessed. The results showed that ATACAmp exhibited higher accuracy than AmpliconArchitect and Circle-finder. Moreover, ATACAmp supported the analysis of single-cell ATAC-seq data, which linked ecDNA to specific cells. Conclusions: ATACAmp, written in Python, is freely available on GitHub under the MIT license: https://github.com/chsmiss/ATAC-amp. Using ATAC-seq data, ATACAmp offers a novel analytical approach that is distinct from the conventional use of WGS data. Thus, this method has the potential to reduce the cost and technical complexity associated ecDNA analysis. [ABSTRACT FROM AUTHOR]

Ovarian cancers encompass a group of neoplasms originating from germinal tissues and exhibiting distinct clinical, pathological, and molecular features. Among these, epithelial ovarian cancers (EOCs) are the most prevalent, comprising five distinct tumor histotypes. Notably, high-grade serous ovarian cancers (HGSOCs) represent the majority, accounting for over 70% of EOC cases. Due to their silent and asymptomatic behavior, HGSOCs are generally diagnosed in advanced stages with an evolved and complex genomic state, characterized by high intratumor heterogeneity (ITH) due to chromosomal instability that distinguishes HGSOCs. Histologically, these cancers exhibit significant morphological diversity both within and between tumors. The histologic patterns associated with solid, endometrioid, and transitional (SET) and classic subtypes of HGSOCs offer prognostic insights and may indicate specific molecular profiles. The evolution of HGSOC from primary to metastasis is typically characterized by clonal ITH, involving shared or divergent mutations in neoplastic sub-clones within primary and metastatic sites. Disease progression and therapy resistance are also influenced by non-clonal ITH, related to interactions with the tumor microenvironment and further genomic changes. Notably, significant alterations occur in nonmalignant cells, including cancer-associated fibroblast and immune cells, during tumor progression. This review provides an overview of the complex nature of HGSOC, encompassing its various aspects of intratumor heterogeneity, histological patterns, and its dynamic evolution during progression and therapy resistance. [ABSTRACT FROM AUTHOR]

Background: Patients with epithelial ovarian carcinoma (EOC) are usually diagnosed at an advanced stage with tumour cell invasion. However, identifying the underlying molecular mechanisms and biomarkers of EOC proliferation and invasion remains challenging. Results: Herein, we explored the relationship between tumour microenvironment (TME) reprogramming and tissue invasion based on single-cell RNA sequencing (scRNA-seq) datasets. Interestingly, hypoxia, oxidative phosphorylation (OXPHOS) and glycolysis, which have biologically active trajectories during epithelial mesenchymal transition (EMT), were positively correlated. Moreover, energy metabolism and anti-apoptotic activity were found to be critical contributors to intratumor heterogeneity. In addition, HMGA1, EGR1 and RUNX1 were found to be critical drivers of the EMT process in EOC. Experimental validation revealed that suppressing EGR1 expression inhibited tumour cell invasion, significantly upregulated the expression of E-cadherin and decreased the expression of N-cadherin. In cell components analysis, cancer-associated fibroblasts (CAFs) were found to significantly contribute to immune infiltration and tumour invasion, and the accumulation of CAFs was associated with poorer patient survival. Conclusion: We revealed the molecular mechanism and biomarkers of tumour invasion and TME reprogramming in EOC, which provides effective targets for the suppression of tumour invasion. [ABSTRACT FROM AUTHOR]

Intratumor heterogeneity (ITH) results from accumulation of somatic mutations in the fractions of successive cancer cell generations. We aimed to use deep sequencing to investigate ITH in colorectal tumors with particular emphasis on variants in oncogenes (ONC) and tumor suppressor genes (TSG). Samples were collected from 16 patients with colorectal cancer and negative or positive lymph node status (n = 8 each). We deep‐sequenced a panel of 56 cancer‐related genes in the central and peripheral locations of T3 size primary tumors and healthy mucosa. The central region of T3 tumors has a different frequency profile and composition of genetic variants. This mutation profile is capable of independently discriminating patients with different lymph node status (p = 0.028) in the central region. We noted an increasing number of mutations outside of the central region of the tumor and a higher number of mutations in tumors from node‐positive patients. Unexpectedly, in the healthy mucosa, we identified somatic mutations with variant allele frequencies, characteristic not only of heterozygotes and homozygotes but also of other discrete peaks (e.g., around 10%, 20%), suggestive of clonal expansion of certain mutant alleles. We found differences in the distribution of variant allele frequencies in TSGs when comparing node‐negative and node‐positive tumors (p = 0.029), as well as central and peripheral regions (p = 0.00399). TSGs may play an important role in the escape of the tumor toward metastatic colonization. [ABSTRACT FROM AUTHOR]

Purpose: Chemotherapy is pivotal in the multimodal treatment of pancreatic ductal adenocarcinoma (PDAC). Technical advances unveiled a high degree of inter- and intratumoral heterogeneity. We hypothesized that intratumoral heterogeneity (ITH) impacts response to gemcitabine treatment and demands specific targeting of resistant subclones. Methods: Using single cell-derived cell lines (SCDCLs) from the classical cell line BxPC3 and the basal-like cell line Panc-1, we addressed the effect of ITH on response to gemcitabine treatment. Results: Individual SCDCLs of both parental tumor cell populations showed considerable heterogeneity in response to gemcitabine. Unsupervised PCA including the 1,000 most variably expressed genes showed a clustering of the SCDCLs according to their respective sensitivity to gemcitabine treatment for BxPC3, while this was less clear for Panc-1. In BxPC3 SCDCLs, enriched signaling pathways EMT, TNF signaling via NfKB, and IL2STAT5 signaling correlated with more resistant behavior to gemcitabine. In Panc-1 SCDCLs MYC targets V1 and V2 as well as E2F targets were associated with stronger resistance. We used recursive feature elimination for Feature Selection in order to compute sets of proteins that showed strong association with the response to gemcitabine. The optimal protein set calculated for Panc-1 comprised fewer proteins in comparison to the protein set determined for BxPC3. Based on molecular profiles, we could show that the gemcitabine-resistant SCDCLs of both BxPC3 and Panc-1 are more sensitive to the BET inhibitor JQ1 compared to the respective gemcitabine-sensitive SCDCLs. Conclusion: Our model system of SCDCLs identified gemcitabine-resistant subclones and provides evidence for the critical role of ITH for treatment response in PDAC. We exploited molecular differences as the basis for differential response and used these for more targeted therapy of resistant subclones. [ABSTRACT FROM AUTHOR]

Background: Current bulk transcriptomic classification systems for bladder cancer do not consider the level of intratumor subtype heterogeneity. Objective: To investigate the extent and possible clinical impact of intratumor subtype heterogeneity across early and more advanced stages of bladder cancer. Design, setting, and participants: We performed single-nucleus RNA sequencing (RNA-seq) of 48 bladder tumors and additional spatial transcriptomics for four of these tumors. Total bulk RNA-seq and spatial proteomics data were available from the same tumors for comparison, along with detailed clinical follow-up of the patients. Outcome measurements and statistical analysis: The primary outcome was progression-free survival for non–muscle-invasive bladder cancer. Cox regression analysis, log-rank tests, Wilcoxon rank-sum tests, Spearman correlation, and Pearson correlation were used for statistical analysis. Results and limitations: We found that the tumors exhibited varying levels of intratumor subtype heterogeneity and that the level of subtype heterogeneity can be estimated from both single-nucleus and bulk RNA-seq data, with high concordance between the two. We found that a higher class 2a weight estimated from bulk RNA-seq data is associated with worse outcome for patients with molecular high-risk class 2a tumors. The sparsity of the data generated using the DroNc-seq sequencing protocol is a limitation. Conclusions: Our results indicate that discrete subtype assignments from bulk RNA-seq data may lack biological granularity and that continuous class scores may improve clinical risk stratification of patients with bladder cancer. Patient summary: We found that several molecular subtypes can exist within a single bladder tumor and that continuous subtype scores can be used to identify a subgroup of patients with poor outcomes. Use of these subtype scores may improve risk stratification for patients with bladder cancer, which can help in making decisions on treatment.

As confusion mounts over RNA isoforms involved in phenotypic plasticity, aberrant CpG methylation-mediated disruption of alternative splicing is increasingly recognized as a driver of intratumor heterogeneity (ITH). Protease serine 3 (PRSS3), possessing four splice variants (PRSS3-SVs; PRSS3-V1–V4), is an indispensable trypsin that shows paradoxical effects on cancer development. Here, we found that PRSS3 transcripts and their isoforms were divergently expressed in lung cancer, exhibiting opposing functions and clinical outcomes, namely, oncogenic PRSS3-V1 and PRSS3-V2 versus tumor-suppressive PRSS3-V3, by targeting different downstream genes. We identified an intragenic CpG island (iCpGI) in PRSS3. Hypermethylation of iCpGI was mediated by UHRF1/DNMT1 complex interference with the binding of myeloid zinc finger 1 (MZF1) to regulate PRSS3 transcription. The garlic-derived compound diallyl trisulfide cooperated with 5-aza-2′-deoxycytidine to exert antitumor effects in lung adenocarcinoma cells through site-specific iCpGI demethylation specifically allowing MZF1 to upregulate PRSS3-V3 expression. Epigenetic silencing of PRSS3-V3 via iCpGI methylation (iCpGIm) in BALF and tumor tissues was associated with early clinical progression in patients with lung cancer but not in those with squamous cell carcinoma or inflammatory disease. Thus, UHRF1/DNMT1–MZF1 axis-modulated site-specific iCpGIm regulates divergent expression of PRSS3-SVs, conferring nongenetic functional ITH, with implications for early detection of lung cancer and targeted therapies.