Explore the vast range of titles available.

The Cancer Genome Atlas (TCGA) is a public funded project that aims to catalogue and discover major cancer-causing genomic alterations to create a comprehensive “atlas” of cancer genomic profiles. So far, TCGA researchers have analysed large cohorts of over 30 human tumours through large-scale genome sequencing and integrated multi-dimensional analyses. Studies of individual cancer types, as well as comprehensive pan-cancer analyses have extended current knowledge of tumorigenesis. A major goal of the project was to provide publicly available datasets to help improve diagnostic methods, treatment standards, and finally to prevent cancer. This review discusses the current status of TCGA Research Network structure, purpose, and achievements.

Background: We aimed to determine the distribution of intrinsic subtypes within HER2-low breast cancer (BC), and to describe the prognostic impact of HER2-low status on survival outcomes. Methods: This is a retrospective, observational study of primary BC extracted from The Cancer Genome Atlas dataset. We described the distribution of PAM50 intrinsic subtypes within HER2-low BC subtype according to hormonal receptor status (positive (HR+) and negative (HR−)). Secondly, we assessed the impact of HER2-low on survival outcomes (progression-free interval (PFI), disease-free interval (DFI), and overall survival (OS)). Results: We analyzed 804 primary BCs, including 410 (51%) HER2-low BCs (336 HR+ and 74 HR−). The proportion of HER2-enriched tumors was higher in the HER2-low/HR− group compared to HER2-low/HR+ (13.7% versus 1.2%, respectively). HER2-enriched tumors were more frequent in HER2-low/HR− and HER2-low/HR+ subtypes, compared to HER2-negative/HR− and HER2-negative/HR+ subtypes, respectively (13.7% versus 1.6% and 1.2% versus 0.5%, respectively). We observed no significant differences in PFI, DFI, and OS between HER2-low subtypes and each non-HER2-low subtype paired by HR status. Conclusions: Our characterization of PAM50 intrinsic subtypes within HER2-low breast cancer may explain the different clinical behaviors and responses to treatment, and ultimately support further investigation of new treatment strategies in the HER2-low category. Moreover, it highlights the importance of considering HR status in the HER2-low category.

Head and neck squamous cell carcinoma (HNSCC) is a major cancer among head and neck malignancies with a limited availability of effective molecularly targeted therapies. The underlying oncogenic mechanisms, however, remain poorly understood. To investigate patient‐specific molecular targets, we established patient‐derived cell (PDC) lines from surgically resected HNSCC tissue samples. We performed comprehensive analyses, including driver gene mutation profiling using a multigene panel, transcriptomic profiling, and karyotyping. Various cancer‐associated genomic alterations, primarily copy number gains, were identified, and these findings were consistent with those of previous studies. Notably, the amplification of EGFR, FGFR2, and CCND1 was associated with their overexpression, suggesting potential tumor driver roles. A PDC with a PIK3CA activating mutation was sensitive to the PI3K inhibitor Alpelisib. We also demonstrated that PDCs harboring chromosome segregation errors were vulnerable to KIF18A deletion and pharmacological inhibition. These results support the value of HNSCC‐derived PDCs as a platform for advances in precision medicine in oncology research.

Endometrial carcinoma represents the most common gynecological cancer in Europe and the USA. Histopathological classification based on tumor morphology and tumor grade has played a crucial role in the management of endometrial carcinoma, allowing a prognostic stratification into distinct risk categories, and guiding surgical and adjuvant therapy. In 2013, The Cancer Genome Atlas (TCGA) Research Network reported a large scale molecular analysis of 373 endometrial carcinomas which demonstrated four categories with distinct clinical, pathologic, and molecular features: POLE/ultramutated (7% of cases) microsatellite instability (MSI)/hypermutated (28%), copy-number low/endometrioid (39%), and copy-number high/serous-like (26%). In the present article, we report a detailed histological and molecular review of all endometrial carcinoma histotypes in light of the current ESGO/ESTRO/ESP guidelines. In particular, we focus on the distribution and prognostic value of the TCGA groups in each histotype.

Recent advances in genomic technology have led to a better understanding of key molecular alterations that underlie glioblastoma (GBM). The current WHO-based classification of GBM is mainly based on histologic features of the tumor, which frequently do not reflect the molecular differences that describe the diversity in the biology of these lesions. The current WHO definition of GBM relies on the presence of high-grade astrocytic neoplasm with the presence of either microvascular proliferation and/or tumor necrosis. High-throughput analyses have identified molecular subtypes and have led to progress in more accurate classification of GBM. These findings, in turn, would result in development of more effective patient stratification, targeted therapeutics, and prediction of patient outcome. While consensus has not been reached on the precise nature and means to sub-classify GBM, it is clear that IDH -mutant GBMs are clearly distinct from GBMs without IDH1/2 mutation with respect to molecular and clinical features, including prognosis. In addition, recent findings in pediatric GBMs regarding mutations in the histone H3F3A gene suggest that these tumors may represent a 3rd major category of GBM, separate from adult primary ( IDH1/2 wt), and secondary ( IDH1/2 mut) GBMs. In this review, we describe major clinically relevant genetic and epigenetic abnormalities in GBM—such as mutations in IDH1/2 , EGFR , PDGFRA, and NF1 genes—altered methylation of MGMT gene promoter, and mutations in hTERT promoter. These markers may be incorporated into a more refined classification system and applied in more accurate clinical decision-making process. In addition, we focus on current understanding of the biologic heterogeneity and classification of GBM and highlight some of the molecular signatures and alterations that characterize GBMs as histologically defined. We raise the question whether IDH-wild type high grade astrocytomas without microvascular proliferation or necrosis might best be classified as GBM, even if they lack the histologic hallmarks as required in the current WHO classification. Alternatively, an astrocytic tumor that fits the current histologic definition of GBM, but which shows an IDH mutation may in fact be better classified as a distinct entity, given that IDH-mutant GBM are quite distinct from a biological and clinical perspective.

CD8 + T cell infiltration is essential for antitumor immunity across cancers while its clinical significance in gastric cancer (GC) remains unclear. This reflects molecular heterogeneity of GC, as defined by The Cancer Genome Atlas (TCGA) into four subtypes: Epstein–Barr virus (EBV)‐positive, microsatellite instability (MSI), chromosomal instability (CIN), and genomically stable (GS), each with distinct immune features. We aimed to characterize distribution, clinical relevance, and immune associations of CD8 + T cell infiltration within this molecular framework. TCGA ( n = 336) and Zhongshan Hospital (ZSHS, n = 455) cohorts were analyzed. CD8 + T cell infiltration and immune features were compared across TCGA subtypes. Prognostic and predictive significance of CD8 + T cells was evaluated in ZSHS cohort. CD8 + T cell infiltration was elevated in the EBV‐positive and MSI subtypes (ZSHS: p = 0.026; TCGA: p < 0.001). In ZSHS cohort, high CD8 + T cell infiltration was associated with better overall survival ( p = 0.040), particularly in the EBV‐positive ( p = 0.036) and CIN ( p = 0.065) subtypes, but not in MSI ( p = 0.440) or GS ( p = 0.860). Notably, low CD8 + T infiltration predicted superior response to adjuvant chemotherapy in MSI patients (HR = 0.210, p = 0.022). Immune profiling revealed associations of CD8 + T cells with antigen presentation in EBV‐positive, tertiary lymphoid structure signatures in CIN, and podoplanin+ cells in GS tumors, instead of neoantigen burden in MSI or pan‐fibroblast TGFβ response signature in GS. CD8 + T cell infiltration demonstrates subtype‐specific prognostic and therapeutic significance in GC—beneficial in EBV‐positive and CIN tumors, and predictive of chemotherapy response in MSI with low infiltration, which accompanied by divergent immune features, reflecting heterogeneous immunological landscape of GC.

Implication By understanding Matrix Metalloprotease (MMP) dysregulation from a pan-cancer perspective, this study sheds light on the diagnostic potentials of MMPs across multiple neoplasms. Background MMPs are intriguing genes related to cancer disease progression, functional promotion of angiogenesis, invasion, metastasis, and avoidance of immune surveillance. Many studies have noted these genes are frequently upregulated in cancer. However, expression patterns of all MMPs and their diagnostic and prognostic potential have not been investigated in a pan-cancer perspective. Methods The Cancer Genome Atlas (TCGA) data were used to evaluate diagnostic and prognostic potential of 24 MMPs in fifteen different cancer types. Gene expression measured by RNA-seq was analyzed by differential expression, hierarchical clustering, and ROC analysis for individual genes and in combination. Results MMP1, MMP9 , MMP10 , MMP11 , and MMP13 were almost universally upregulated across all cancers, with significant ( p  < 0.05) fold change (FC > 2) in ten of fifteen cancers. MMP3 , MMP7 , MMP12 and MMP14 ) are significantly up-regulated in at least 10 cancer types. Interestingly, MMP2 , MMP7 , MMP23B , MMP27 and MMP28 ) are significantly down-regulated in seven to nine cancer types. Multiple MMPs possess AUC’s > 0.9 in more than one cancer. However, survival analyses suggest that the prognostic value of MMPs is limited to clear cell renal carcinoma. Conclusions Most MMPs have consistently increased gene expression across cancers, while several MMPs have consistently decreased expression in several cancer types. Many MMPs have diagnostic value individually or in combination, while the prognostic value of MMPs is restricted to one subtype of kidney cancer.

Resistance to anoikis is a key characteristic of many cancer cells, promoting cell survival. However, the mechanism of anoikis in hepatocellular carcinoma (HCC) remains unknown. In this study, we applied differentially expressed overlapping anoikis-related genes to classify The Cancer Genome Atlas (TCGA) samples using an unsupervised cluster algorithm. Then, we employed weighted gene coexpression network analysis (WGCNA) to identify highly correlated genes and constructed a prognostic risk model based on univariate Cox proportional hazards regression. This model was validated using external datasets from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). Finally, we used a CIBERSORT algorithm to investigate the correlation between risk score and immune infiltration. Our results showed that the TCGA cohorts could be divided into two subgroups, with subgroup A having a lower survival probability. Five genes (BAK1, SPP1, BSG, PBK and DAP3) were identified as anoikis-related prognostic genes. Moreover, the prognostic risk model effectively predicted overall survival, which was validated using ICGC and GEO datasets. In addition, there was a strong correlation between infiltrating immune cells and prognostic genes and risk score. In conclusion, we identified anoikis-related subgroups and prognostic genes in HCC, which could be significant for understanding the molecular mechanisms and treatment of HCC.

Background Pan-cancer analysis examines both the commonalities and heterogeneity among genomic and cellular alterations across numerous types of tumors. Pan-cancer analysis of gene expression, tumor mutational burden (TMB), microsatellite instability (MSI), and tumor immune microenvironment (TIME), and methylation becomes available based on the multi-omics data from The Cancer Genome Atlas Program (TCGA). Some online tools provide analysis of gene and protein expression, mutation, methylation, and survival for TCGA data. However, these online tools were either Uni-functional or were not able to perform analysis of user-defined functions. Therefore, we created the TCGAplot R package to facilitate perform pan-cancer analysis and visualization of the built-in multi-omic TCGA data. Results TCGAplot provides several functions to perform pan-cancer paired/unpaired differential gene expression analysis, pan-cancer correlation analysis between gene expression and TMB, MSI, TIME, and promoter methylation. Functions for visualization include paired/unpaired boxplot, survival plot, ROC curve, heatmap, scatter, radar chart, and forest plot. Moreover, gene set based pan-cancer and tumor specific analyses were also available. Finally, all these built-in multi-omic data could be extracted for implementation for user-defined functions, making the pan-cancer analysis much more convenient.\\ Conclusions We developed an R-package for integrative pan-cancer analysis and visualization of TCGA multi-omics data. The source code and pre-built package are available at GitHub ( https://github.com/tjhwangxiong/TCGAplot ).

Background HER2-low breast cancer (BC) is currently an area of active interest. This study evaluated the impact of low expression of HER2 on survival outcomes in HER2-negative non-metastatic breast cancer (BC). Methods Patients with HER2-negative non-metastatic BC from 6 centres within the Asian Breast Cancer Cooperative Group (ABCCG) ( n = 28,280) were analysed. HER2-low was defined as immunohistochemistry (IHC) 1+ or 2+ and in situ hybridization non-amplified (ISH−) and HER2-zero as IHC 0. Relapse-free survival (RFS) and overall survival (OS) by hormone receptor status and HER2 IHC 0, 1+ and 2+ ISH− status were the main outcomes. A combined TCGA-BRCA and METABRIC cohort ( n = 1967) was also analysed to explore the association between HER2 expression, ERBB2 copy number variation (CNV) status and RFS. Results ABCCG cohort median follow-up was 6.6 years; there were 12,260 (43.4%) HER2-low BC and 16,020 (56.6%) HER2-zero BC. The outcomes were better in HER2-low BC than in HER2-zero BC (RFS: centre-adjusted hazard ratio (HR) 0.88, 95% CI 0.82–0.93, P < 0.001; OS: centre-adjusted HR 0.82, 95% CI 0.76–0.89, P < 0.001). On multivariable analysis, HER2-low status was prognostic (RFS: HR 0.90, 95% CI 0.85–0.96, P = 0.002; OS: HR 0.86, 95% CI 0.79–0.93, P < 0.001). These differences remained significant in hormone receptor-positive tumours and for OS in hormone receptor-negative tumours. Superior outcomes were observed for HER2 IHC1+ BC versus HER2-zero BC (RFS: HR 0.89, 95% CI 0.83–0.96, P = 0.001; OS: HR 0.85, 95% CI 0.78–0.93, P = 0.001). No significant differences were seen between HER2 IHC2+ ISH− and HER2-zero BCs. In the TCGA-BRCA and METABRIC cohorts, ERBB2 CNV status was an independent RFS prognostic factor (neutral versus non-neutral HR 0.71, 95% CI 0.59–0.86, P < 0.001); no differences in RFS by ERBB2 mRNA expression levels were found. Conclusions HER2-low BC had a superior prognosis compared to HER2-zero BC in the non-metastatic setting, though absolute differences were modest and driven by HER2 IHC 1+ BC. ERBB2 CNV merits further investigation in HER2-negative BC.