Systematic investigation of the prognostic impact of clonal status of somatic mutations across multiple cancer types.

Tumors are genetically heterogeneous and many mutations are actually present in subclonal populations. The clonal status of mutations is valuable for accurate prognosis, clinical management. The aim of this study was to identify the clonal status of somatic mutations and systematically evaluate their prognostic values across various cancer types. We totally identified 227 clonal and 432 subclonal mutations contributed to prognosis and demonstrated the importance of clonal status in improving mutation-related clinical guidance. We further developed a customized multi-step approach to identify gene-specific prognostic patterns of clonal status at pan-cancer level and found some cancer-specific prognostic patterns. The 'subclonal-dependent risk' subpattern was one of the most common subpatterns, it usually accompanied by high genomic in-stability and high extent of intra-tumor heterogeneity and could be used to improve the accuracy of prognostic analysis. Our results revealed the importance of clonal status, especially subclonal mutation in clinical survival.

Comprehensive characterization of clonality of driver genes revealing their clinical relevance in colorectal cancer.

BACKGROUND: Genomic studies of colorectal cancer have revealed the complex genomic heterogeneity of the tumor. The acquisition and selection of genomic alterations may be critical to understanding the initiation and progression of this disease. METHODS: In this study, we have systematically characterized the clonal architecture of 97 driver genes in 536 colorectal cancer patients from TCGA. RESULTS: A high proportion of clonal mutations in 93 driver genes were observed. 40 genes showed significant associations between their clonality and multiple clinicopathologic factors. Kaplan-Meier analysis suggested that the mutation clonality of ANK1, CASP8, SMAD2, and ARID1A had a significant impact on the CRC patients' outcomes. Multivariable analysis revealed that subclonal ANK1 mutations, clonal CASP8 mutations, and clonal SMAD2 mutations independently predicted for shorter overall survival after adjusting for clinicopathological factors. The poor outcome of the subclonal ANK1 mutation may be caused by upregulation of IL4I1, IDO1, IFNG and MAPK12 which showed potential roles in tumor immune evasion through accumulation of immunosuppressive cells such as regulatory T cells and myeloid derived suppressor cells. CONCLUSION: These results suggested that the clonality of driver genes could act as prognostic markers and potential therapeutic targets in human colorectal cancer.

Cancer-related gene mutations and intratumoral genetic heterogeneity in human epidermal growth factor receptor 2 heterogeneous gastric cancer.

Human epidermal growth factor receptor 2 (HER2) protein overexpression is associated with HER2 gene amplification, a critical driver oncogenetic change in gastric cancer. HER2 heterogeneity in advanced gastric cancer is associated with a poor prognosis and affects the clinical efficacy of trastuzumab. However, the mechanisms of HER2 heterogeneity are not fully understood. Here, we examined whether HER2 heterogeneous gastric cancer exhibited intratumoral genetic heterogeneity in other cancer-related genes. Two cases of advanced gastric cancer with HER2 heterogeneity were selected, and samples of HER2-positive and HER2-negative areas in each case were analyzed using a cancer-associated multiple gene panel. In both cases, TP53 mutations were observed in both HER2-positive and HER2-negative areas, whereas many of the potential driver and passenger mutations differed between HER2-positive and HER2-negative areas. Overall, our findings demonstrated that HER2 heterogeneous gastric cancer exhibited intratumoral genetic heterogeneity in other cancer-related genes and that the molecular mechanisms could differ between HER2-positive and -negative areas.

Revealing clonality and subclonality of driver genes for clinical survival benefits in breast cancer.

PURPOSE: Genomic studies have revealed that genomic aberrations play important roles in the progression of this disease. The aim of this study was to evaluate the associations between clinical survival outcomes of the clonality and subclonality status of driver genes in breast cancer. METHODS: We performed an integrated analysis to infer the clonal status of 55 driver genes in breast cancer data from TCGA. We used the chi-squared test to assess the relations between clonality of driver gene mutations and clinicopathological factors. The Kaplan-Meier method was performed for the visualization and the differences between survival curves were calculated by log-rank test. Univariate and multivariate Cox proportional hazards regression models were used to adjust for clinicopathological factors. RESULTS: We identified a high proportion of clonal mutations in these driver genes. Among them, there were 17 genes showing significant associations between their clonality and multiple clinicopathologic factors. Performing survival analysis on BRCA patients with clonal or subclonal driver gene mutations, we found that clonal ERBB2, FOXA1, and KMT2C mutations and subclonal GATA3 and RB1 mutations predicted shorter overall survival compared with those with wild type. Furthermore, clonal ERBB2 and FOXA1 mutations and subclonal GATA3 and RB1 mutations independently predicted for shorter overall survival after adjusting for clinicopathological factors. By longitudinal analysis, the clonality of ERBB2, FOXA1, GATA3, and RB1 significantly predicted patients' outcome within some specific BRCA tumor stages and histological subtypes. CONCLUSIONS: In summary, these clonal or subclonal mutations of driver genes have implications for diagnosis, prognosis, and treatment with BRCA patients.

The prognostic impact of subclonal IDH1 mutation in grade 2-4 astrocytomas.

Background: Isocitrate dehydrogenase (IDH) mutations are thought to represent an early oncogenic event in glioma evolution, found with high penetrance across tumor cells; however, in rare cases, IDH mutation may exist only in a small subset of the total tumor cells (subclonal IDH mutation). Methods: We present 2 institutional cases with subclonal IDH1 R132H mutation. In addition, 2 large publicly available cohorts of IDH-mutant astrocytomas were mined for cases harboring subclonal IDH mutations (defined as tumor cell fraction with IDH mutation ≤0.67) and the clinical and molecular features of these subclonal cases were compared to clonal IDH-mutant astrocytomas. Results: Immunohistochemistry (IHC) performed on 2 institutional World Health Organization grade 4 IDH-mutant astrocytomas revealed only a minority of tumor cells in each case with IDH1 R132H mutant protein, and next-generation sequencing (NGS) revealed remarkably low IDH1 variant allele frequencies compared to other pathogenic mutations, including TP53 and/or ATRX. DNA methylation classified the first tumor as high-grade IDH-mutant astrocytoma with high confidence (0.98 scores). In the publicly available datasets, subclonal IDH mutation was present in 3.9% of IDH-mutant astrocytomas (18/466 tumors). Compared to clonal IDH-mutant astrocytomas (n = 156), subclonal cases demonstrated worse overall survival in grades 3 (P = .0106) and 4 (P = .0184). Conclusions: While rare, subclonal IDH1 mutations are present in a subset of IDH-mutant astrocytomas of all grades, which may lead to a mismatch between IHC results and genetic/epigenetic classification. These findings suggest a possible prognostic role of IDH mutation subclonality, and highlight the potential clinical utility of quantitative IDH1 mutation evaluation by IHC and NGS.

Identification of mutational signature for lung adenocarcinoma prognosis and immunotherapy prediction.

There is no robust genomic signature to predict the prognosis of patients with early-stage lung adenocarcinoma (LUAD). It was known that clonal heterogeneity was closely associated to tumour progression and prognosis prediction. Herein, using stage I patients from The Cancer Genome Atlas, we identified the clonal/subclonal events of each gene and preselected a set of genes with prognosis-specific mutation patterns based on a robust published transcriptomic prognostic signature. Subsequently, we constructed a mutational prognostic signature (MPS), whose prognostic performance was independently validated in two datasets of stage I samples. The predicted high-risk patients had significantly higher immune cell infiltration, along with higher expression of cytotoxic and immune checkpoint genes, and an integrated dataset with 88 samples confirmed that high-risk patients could benefit from immunotherapy. The developed MPS can identify the high-risk patients with stage I LUAD and improve individualised treatment planning of high-risk patients who might benefit from immunotherapy. KEY MESSAGES: We creatively developed a prognostic signature (57-MPS) based on clonal diversity. The high-risk samples displayed an underlying immunosuppressive mechanism. 57-MPS improved the predictive performance of PD-L1 for immunotherapy.

Multi-site tumor sampling highlights molecular intra-tumor heterogeneity in malignant pleural mesothelioma.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a heterogeneous cancer. Better knowledge of molecular and cellular intra-tumor heterogeneity throughout the thoracic cavity is required to develop efficient therapies. This study focuses on molecular intra-tumor heterogeneity using the largest series to date in MPM and is the first to report on the multi-omics profiling of a substantial series of multi-site tumor samples. METHODS: Intra-tumor heterogeneity was investigated in 16 patients from whom biopsies were taken at distinct anatomical sites. The paired biopsies collected from apex, side wall, costo-diaphragmatic, or highest metabolic sites as well as 5 derived cell lines were screened using targeted sequencing. Whole exome sequencing, RNA sequencing, and DNA methylation were performed on a subset of the cohort for deep characterization. Molecular classification, recently defined histo-molecular gradients, and cell populations of the tumor microenvironment were assessed. RESULTS: Sequencing analysis identified heterogeneous variants notably in NF2, a key tumor suppressor gene of mesothelial carcinogenesis. Subclonal tumor populations were shared among paired biopsies, suggesting a polyclonal dissemination of the tumor. Transcriptome analysis highlighted dysregulation of cell adhesion and extracellular matrix pathways, linked to changes in histo-molecular gradient proportions between anatomic sites. Methylome analysis revealed the contribution of epigenetic mechanisms in two patients. Finally, significant changes in the expression of immune mediators and genes related to immunological synapse, as well as differential infiltration of immune populations in the tumor environment, were observed and led to a switch from a hot to a cold immune profile in three patients. CONCLUSIONS: This comprehensive analysis reveals patient-dependent spatial intra-tumor heterogeneity at the genetic, transcriptomic, and epigenetic levels and in the immune landscape of the tumor microenvironment. Results support the need for multi-sampling for the implementation of molecular-based precision medicine.