bims-tumhet 2024-09-08 papers

bims-tumhet

Biomed News

on Tumor Heterogeneity

Issue of 2024‒09‒08
seven papers selected by
Sergio Marchini, Humanitas Research

Molecular classification of ovarian high-grade serous/endometrioid carcinomas through multi-omics analysis: JGOG3025-TR2 study.
Changes in the tumor immune microenvironment during disease progression in clear cell ovarian cancer.
Immunotherapy for ovarian cancer: towards a tailored immunophenotype-based approach.
Large-scale analysis of whole genome sequencing data from formalin-fixed paraffin-embedded cancer specimens demonstrates preservation of clinical utility.
Tracking clonal evolution of drug resistance in ovarian cancer patients by exploiting structural variants in cfDNA.
Cancer cell states: Lessons from ten years of single-cell RNA-sequencing of human tumors.
Exploring the impact of intra-tumoural heterogeneity on liquid biopsy cell-free DNA methylation and copy number in head and neck squamous cell carcinoma.

Br J Cancer. 2024 Aug 30.

Molecular classification of ovarian high-grade serous/endometrioid carcinomas through multi-omics analysis: JGOG3025-TR2 study.

Shiro Takamatsu, R Tyler Hillman, Kosuke Yoshihara, Tsukasa Baba, Muneaki Shimada, Hiroshi Yoshida, Hiroaki Kajiyama, Katsutoshi Oda, Masaki Mandai, Aikou Okamoto, Takayuki Enomoto, Noriomi Matsumura.

BACKGROUND: Considerable interobserver variability exists in diagnosis of ovarian high-grade endometrioid carcinoma (HGEC) and high-grade serous carcinoma (HGSC) due to histopathological similarities. While homologous recombination deficiency (HRD) correlates with drug sensitivity in HGSC, the molecular features of HGEC are unclear.METHODS: Fresh-frozen samples from 15 ovarian HGECs and 274 ovarian HGSCs in the JGOG-TR2 cohort were submitted to targeted DNA sequencing, RNA sequencing, DNA methylation array, and SNP array. We additionally analyzed 555 ovarian HGSCs from TCGA-OV and 287 endometrial high-grade carcinomas from TCGA-UCEC.
RESULTS: Unsupervised clustering using copy number signatures identified four distinct tumor groups (C1, C2, C3 and C4). C1 (n = 41) showed CCNE1 amplification and poor survival. C2 (n = 160) and C3 (n = 59) showed high BRCA1/2 alteration frequency with low and moderate ploidy, respectively. C4 (n = 22) was characterized by favorable outcome, higher HGEC proportion, no BRCA1/2 alteration or CCNE1 amplification, and low levels of HRD score, ploidy, intra-tumoral heterogeneity, cell proliferation rate, and WT1 gene expression. Notably, C4 exhibited a normal endometrium-like DNA methylation profile, thus, defined as "HGEC-type" tumors, which were also identified in TCGA-OV and TCGA-UCEC.
CONCLUSIONS: Ovarian "HGEC-type" tumors present a non-HRD status, favorable prognosis, and endometrial differentiation, possibly constituting a subset of clinically diagnosed HGSCs.

DOI: https://doi.org/10.1038/s41416-024-02837-x
Int J Gynecol Cancer. 2024 Sep 04. pii: ijgc-2024-005662. [Epub ahead of print]

Changes in the tumor immune microenvironment during disease progression in clear cell ovarian cancer.

Ha Young Woo, Na Yeon Kim, Jinok Jun, Jung-Yun Lee, Eun Ji Nam, Sang Wun Kim, Sung-Hoon Kim, Young-Tae Kim, Yong Jae Lee.

  OBJECTIVE: The tumor immune microenvironment in ovarian clear cell carcinoma has not been clearly defined. We analyzed the immunological changes from treatment-naive to recurrence to correlate them with clinical outcomes.METHOD: We compared the changes in immune infiltration of advanced-stage ovarian clear cell carcinoma samples before treatment and at the time of recurrence via immunohistochemistry (Programmed Cell Death-ligand 1 (PD-L1), cluster of differentiation 8 (CD8+), forkhead box P3 (Foxp3+)), tumor-infiltrating lymphocytes (TIL), and next-generation sequencing (54 patients). We analyzed the association between platinum sensitivity status and tumor immune microenvironment.
RESULTS: Immunohistochemistry revealed significantly increased PD-L1 (p=0.048) and CD8+T cells (p=0.022) expression levels after recurrence. No significant differences were observed in TIL density or Foxp3+T cells. There was no significant correlation between TIL, PD-L1, CD8+T cell, and Foxp3+T cell levels in treatment-naive tumors and survival outcomes. The most common genomic alterations were PIK3CA (41.7%) and ARID1A (41.7%) mutations. There were no differences in the immunological changes or survival outcomes according to PIK3CA and ARID1A mutations. Patients with recurrent platinum-sensitive disease showed higher TIL expression levels. There were no significant differences in PD-L1, CD8+T cells, or Foxp3+T cells between platinum-sensitive and platinum-resistant diseases.
CONCLUSION: We characterized the tumor immune microenvironment in patients with advanced-stage ovarian clear cell carcinoma. PD-L1 and CD8+T cell expression significantly increased after recurrence. Whether this could be used to select patients for immunotherapy in the recurrence setting should be investigated.

Keywords:  Ovarian Cancer

DOI:  https://doi.org/10.1136/ijgc-2024-005662
Nat Rev Clin Oncol. 2024 Sep 04.

Immunotherapy for ovarian cancer: towards a tailored immunophenotype-based approach.

Eleonora Ghisoni, Matteo Morotti, Apostolos Sarivalasis, Alizée J Grimm, Lana Kandalaft, Denarda Dangaj Laniti, George Coukos.

Despite documented evidence that ovarian cancer cells express immune-checkpoint molecules, such as PD-1 and PD-L1, and of a positive correlation between the presence of tumour-infiltrating lymphocytes and favourable overall survival outcomes in patients with this tumour type, the results of trials testing immune-checkpoint inhibitors (ICIs) in these patients thus far have been disappointing. The lack of response to ICIs can be attributed to tumour heterogeneity as well as inherent or acquired resistance associated with the tumour microenvironment (TME). Understanding tumour immunobiology, discovering biomarkers for patient selection and establishing optimal treatment combinations remains the hope but also a key challenge for the future application of immunotherapy in ovarian cancer. In this Review, we summarize results from trials testing ICIs in patients with ovarian cancer. We propose the implementation of a systematic CD8+ T cell-based immunophenotypic classification of this malignancy, followed by discussions of the preclinical data providing the basis to treat such immunophenotypes with combination immunotherapies. We posit that the integration of an accurate TME immunophenotype characterization with genetic data can enable the design of tailored therapeutic approaches and improve patient recruitment in clinical trials. Lastly, we propose a roadmap incorporating tissue-based profiling to guide future trials testing adoptive cell therapy approaches and assess novel immunotherapy combinations while promoting collaborative research.

DOI: https://doi.org/10.1038/s41571-024-00937-4
Nat Commun. 2024 Sep 04. 15(1): 7731

Large-scale analysis of whole genome sequencing data from formalin-fixed paraffin-embedded cancer specimens demonstrates preservation of clinical utility.

PARTNER Trial Group

Whole genome sequencing (WGS) provides comprehensive, individualised cancer genomic information. However, routine tumour biopsies are formalin-fixed and paraffin-embedded (FFPE), damaging DNA, historically limiting their use in WGS. Here we analyse FFPE cancer WGS datasets from England's 100,000 Genomes Project, comparing 578 FFPE samples with 11,014 fresh frozen (FF) samples across multiple tumour types. We use an approach that characterises rather than discards artefacts. We identify three artefactual signatures, including one known (SBS57) and two previously uncharacterised (SBS FFPE, ID FFPE), and develop an "FFPEImpact" score that quantifies sample artefacts. Despite inferior sequencing quality, FFPE-derived data identifies clinically-actionable variants, mutational signatures and permits algorithmic stratification. Matched FF/FFPE validation cohorts shows good concordance while acknowledging SBS, ID and copy-number artefacts. While FF-derived WGS data remains the gold standard, FFPE-samples can be used for WGS if required, using analytical advancements developed here, potentially democratising whole cancer genomics to many.

DOI: https://doi.org/10.1038/s41467-024-51577-2
bioRxiv. 2024 Aug 23. pii: 2024.08.21.609031. [Epub ahead of print]

Tracking clonal evolution of drug resistance in ovarian cancer patients by exploiting structural variants in cfDNA.

Marc J Williams, Ignacio Vázquez-García, Grittney Tam, Michelle Wu, Nancy Varice, Eliyahu Havasov, Hongyu Shi, Gryte Satas, Hannah J Lees, Jake June-Koo Lee, Matthew A Myers, Matthew Zatzman, Nicole Rusk, Emily Ali, Ronak H Shah, Michael F Berger, Neeman Mohibullah, Yulia Lakhman, Dennis S Chi, Nadeem R Abu-Rustum, Carol Aghajanian, Andrew McPherson, Dmitriy Zamarin, Brian Loomis, Britta Weigelt, Claire F Friedman, Sohrab P Shah.

Drug resistance is the major cause of therapeutic failure in high-grade serous ovarian cancer (HGSOC). Yet, the mechanisms by which tumors evolve to drug resistant states remains largely unknown. To address this, we aimed to exploit clone-specific genomic structural variations by combining scaled single-cell whole genome sequencing with longitudinally collected cell-free DNA (cfDNA), enabling clonal tracking before, during and after treatment. We developed a cfDNA hybrid capture, deep sequencing approach based on leveraging clone-specific structural variants as endogenous barcodes, with orders of magnitude lower error rates than single nucleotide variants in ctDNA (circulating tumor DNA) detection, demonstrated on 19 patients at baseline. We then applied this to monitor and model clonal evolution over several years in ten HGSOC patients treated with systemic therapy from diagnosis through recurrence. We found drug resistance to be polyclonal in most cases, but frequently dominated by a single high-fitness and expanding clone, reducing clonal diversity in the relapsed disease state in most patients. Drug-resistant clones frequently displayed notable genomic features, including high-level amplifications of oncogenes such as CCNE1 , RAB25 , NOTCH3 , and ERBB2 . Using a population genetics Wright-Fisher model, we found evolutionary trajectories of these features were consistent with drug-induced positive selection. In select cases, these alterations impacted selection of secondary lines of therapy with positive patient outcomes. For cases with matched single-cell RNA sequencing data, pre-existing and genomically encoded phenotypic states such as upregulation of EMT and VEGF were linked to drug resistance. Together, our findings indicate that drug resistant states in HGSOC pre-exist at diagnosis and lead to dramatic clonal expansions that alter clonal composition at the time of relapse. We suggest that combining tumor single cell sequencing with cfDNA enables clonal tracking in patients and harbors potential for evolution-informed adaptive treatment decisions.

DOI: https://doi.org/10.1101/2024.08.21.609031
Cancer Cell. 2024 Aug 28. pii: S1535-6108(24)00304-0. [Epub ahead of print]

Cancer cell states: Lessons from ten years of single-cell RNA-sequencing of human tumors.

Itay Tirosh, Mario L Suva.

Human tumors are intricate ecosystems composed of diverse genetic clones and malignant cell states that evolve in a complex tumor micro-environment. Single-cell RNA-sequencing (scRNA-seq) provides a compelling strategy to dissect this intricate biology and has enabled a revolution in our ability to understand tumor biology over the last ten years. Here we reflect on this first decade of scRNA-seq in human tumors and highlight some of the powerful insights gleaned from these studies. We first focus on computational approaches for robustly defining cancer cell states and their diversity and highlight some of the most common patterns of gene expression intra-tumor heterogeneity (eITH) observed across cancer types. We then discuss ambiguities in the field in defining and naming such eITH programs. Finally, we highlight critical developments that will facilitate future research and the broader implementation of these technologies in clinical settings.

DOI: https://doi.org/10.1016/j.ccell.2024.08.005
Oral Oncol. 2024 Sep 04. pii: S1368-8375(24)00329-4. [Epub ahead of print]158 107011

Exploring the impact of intra-tumoural heterogeneity on liquid biopsy cell-free DNA methylation and copy number in head and neck squamous cell carcinoma.

Karl Payne, Harini Suriyanarayanan, Jill Brooks, Hisham Mehanna, Paul Nankivell, Deena Gendoo.

  Liquid biopsy profiling is gaining increasing promise towards biomarker-led identification and disease stratification of tumours, particularly for tumours displaying significant intra-tumoural heterogeneity (ITH). For head and neck squamous cell carcinoma (HNSCC), which display high levels of genetic ITH, identification of epigenetic modifications and methylation signatures has shown multiple uses in stratification of HNSCC for prognosis, treatment, and HPV status. In this study, we investigated the potential of liquid biopsy methylomics and genomic copy number to profile HNSCC. We conducted multi-region sampling of tumour core, tumour margin and normal adjacent mucosa, as well as plasma cell-free DNA (cfDNA) across 9 HNSCC patients. Collectively, our work highlights the prevalence of methylomic ITH in HNSCC, and demonstrates the potential of cfDNA methylation as a tool for ITH assessment and serial sampling.

Keywords:  Bioinformatics; Clinical; Copy number; HNSCC; Liquid biopsy; Methylation; Multi-omic; Profiling; Translational; Tumour heterogeneity

DOI:  https://doi.org/10.1016/j.oraloncology.2024.107011