bims-tumhet 2024-08-11 papers

Issue of 2024–08–11
ten papers selected by
Sergio Marchini, Humanitas Research

Curr Oncol Rep. 2024 Aug 08.

Prevention of Ovarian Cancer: Where are We Now and Where are We Going?

Isabel V Rodriguez, Talayeh Ghezelayagh, Kathryn P Pennington, Barbara M Norquist.

PURPOSE OF REVIEW: To describe current and future strategies to reduce the burden of ovarian cancer through prevention.
RECENT FINDINGS: Current strategies in genetic testing are missing a substantial number of individuals at risk, representing a missed opportunity for ovarian cancer prevention. Past efforts at screening and early detection have thus far failed to improve ovarian cancer mortality, and novel techniques are needed. Surgical prevention is highly effective, but surgical menopause from oophorectomy has significant side effects. Novel surgical strategies aimed at reducing risk while minimizing these harms are currently being studied. To maximize ovarian cancer prevention, a multi-pronged approach is needed. We propose that more inclusive and accurate genetic testing to identify more individuals at risk, novel molecular screening and early detection, surgical prevention that maximizes quality of life while reducing risk, and broader adoption of targeted and opportunistic salpingectomy will together reduce the burden of ovarian cancer.

Keywords: BRCA ; Cancer prevention; Genetic testing; Inherited risk; Ovarian cancer; Salpingectomy

DOI: https://doi.org/10.1007/s11912-024-01587-6

Cancer Immunol Res. 2024 Aug 08.

The spatial structure of the tumor immune microenvironment can explain and predict patient response in high-grade serous carcinoma.

Lucy B Van Kleunen, Mansooreh Ahmadian, Miriam D Post, Rebecca J Wolsky, Chrisitan Rickert, Kimberly R Jordan, Junxiao Hu, Jennifer K Richer, Lindsay W Brubaker, Nicole Marjon, Kian Behbakht, Matthew J Sikora, Benjamin G Bitler, Aaron Clauset.

Ovarian cancer is the deadliest gynecological malignancy, and therapeutic options and mortality rates over the last three decades have largely not changed. Recent studies indicate that the composition of the tumor immune microenvironment (TIME) influences patient outcomes. To improve spatial understanding of the TIME, we performed multiplexed ion beam imaging on 83 human high-grade serous carcinoma tumor samples, identifying about 160,000 cells across 23 cell types. For 77 of these samples meeting inclusion criteria, we generated composition features based on cell type proportions, spatial features based on the distances between cell types, and spatial network features representing cell interactions and cell clustering patterns, which we linked to traditional clinical and immunohistochemical variables and patient overall survival (OS) and progression-free survival (PFS) outcomes. Among these features, we found several significant univariate correlations, including B-cell contact with M1 macrophages (OS hazard ratio HR=0.696, p=0.011, PFS HR=0.734, p=0.039). We then used high-dimensional random forest models to evaluate out-of-sample predictive performance for OS and PFS outcomes and to derive relative feature importance scores for each feature. The top model for predicting low or high PFS used TIME composition and spatial features and achieved an average AUC (area under the receiver-operating characteristic curve) score of 0.71. The results demonstrate the importance of spatial structure in understanding how the TIME contributes to treatment outcomes. Furthermore, the present study provides a generalizable roadmap for spatial analyses of the TIME in ovarian cancer research.

DOI: https://doi.org/10.1158/2326-6066.CIR-23-1109

Am J Transl Res. 2024 ;16(7): 3338-3354

Single-cell RNA sequencing in ovarian cancer: revealing new perspectives in the tumor microenvironment.

Qiannan Zhao, Huaming Shao, Tianmei Zhang.

Single-cell sequencing technology has emerged as a pivotal tool for unraveling the complexities of the ovarian tumor microenvironment (TME), which is characterized by its cellular heterogeneity and intricate cell-to-cell interactions. Ovarian cancer (OC), known for its high lethality among gynecologic malignancies, presents significant challenges in treatment and diagnosis, partly due to the complexity of its TME. The application of single-cell sequencing in ovarian cancer research has enabled the detailed characterization of gene expression profiles at the single-cell level, shedding light on the diverse cell populations within the TME, including cancer cells, stromal cells, and immune cells. This high-resolution mapping has been instrumental in understanding the roles of these cells in tumor progression, invasion, metastasis, and drug resistance. By providing insight into the signaling pathways and cell-to-cell communication mechanisms, single-cell sequencing facilitates the identification of novel therapeutic targets and the development of personalized medicine approaches. This review summarizes the advancement and application of single-cell sequencing in studying the stromal components and the broader TME in OC, highlighting its implications for improving diagnosis, treatment strategies, and understanding of the disease's underlying biology.

Keywords: Ovarian cancer; complementary treatment; single-cell sequencing; tumor microenvironment

DOI: https://doi.org/10.62347/SMSG9047

Transl Res. 2024 Aug 05. pii: S1931-5244(24)00146-4. [Epub ahead of print]

The unveiled Mosaic of Intra-Tumor Heterogeneity in Ovarian Cancer Through Spatial Transcriptomic Technologies: a systematic review.

Laura Masatti, Matteo Marchetti, Stefania Pirrotta, Giulia Spagnol, Anna Corrà, Jacopo Ferrari, Marco Noventa, Carlo Saccardi, Enrica Calura, Roberto Tozzi.

Epithelial ovarian cancer is a significant global health issue among women. Diagnosis and treatment pose challenges due to difficulties in predicting patient responses to therapy, primarily stemming from gaps in understanding tumor chemoresistance mechanisms. Recent advancements in transcriptomic technologies like single-cell RNA sequencing and spatial transcriptomics have greatly improved our understanding of ovarian cancer intratumor heterogeneity and tumor microenvironment composition. Spatial transcriptomics, in particular, comprises a plethora of technologies that enable the detection of hundreds of transcriptomes and their spatial distribution within a histological section, facilitating the study of cell types, states, and interactions within the tumor and its microenvironment. Studies investigating the spatial distribution of gene expression in ovarian cancer masses have identified specific features that impact prognosis and therapy outcomes. Emerging evidence suggests that specific spatial patterns of tumor cells and their immune and non-immune microenvironment significantly influence therapy response, as well as the behavior and progression of primary tumors and metastatic sites. The importance of spatially contextualizing ovarian cancer transcriptomes is underscored by these findings, which will advance our understanding and therapeutic approaches for this complex disease.

DOI: https://doi.org/10.1016/j.trsl.2024.08.001

Bioimpacts. 2024 ;14(4): 29957

Cancer treatment comes to age: from one-size-fits-all to next-generation sequencing (NGS) technologies.

Sepideh Parvizpour, Hanieh Beyrampour-Basmenj, Jafar Razmara, Farhad Farhadi, Mohd Shahir Shamsir.

Cancer is one of the leading causes of death worldwide and one of the greatest challenges in extending life expectancy. The paradigm of one-size-fits-all medicine has already given way to the stratification of patients by disease subtypes, clinical characteristics, and biomarkers (stratified medicine). The introduction of next-generation sequencing (NGS) in clinical oncology has made it possible to tailor cancer patient therapy to their molecular profiles. NGS is expected to lead the transition to precision medicine (PM), where the right therapeutic approach is chosen for each patient based on their characteristics and mutations. Here, we highlight how the NGS technology facilitates cancer treatment. In this regard, first, precision medicine and NGS technology are reviewed, and then, the NGS revolution in precision medicine is described. In the sequel, the role of NGS in oncology and the existing limitations are discussed. The available databases and bioinformatics tools and online servers used in NGS data analysis are also reviewed. The review ends with concluding remarks.

Keywords: Cancer; Next-generation sequencing; One-size-fits-all medicine; Personalized medicine; Precision medicine; Stratified medicine

DOI: https://doi.org/10.34172/bi.2023.29957

Mol Oncol. 2024 Aug 07.

Precision Cancer Medicine 2.0-Oncology in the postgenomic era.

Riccardo Masina, Carlos Caldas.

Genomic medicine has transformed the lives of patients with cancer by enabling individualised and evidence-based clinical decision-making. Despite this progress, the implementation of precision cancer medicine is limited by its dependence on isolated biomarkers. The development of bulk and single-cell multiomic technologies has revealed the enormous complexity of the cancer ecosystem. Beyond the cancer cell, the tumour microenvironment, macroenvironment and host factors, including the microbiome, profoundly influence the cancer phenotype, and accounting for these enhances the resolution of precision medicine. The advent of robust multiomic profiling and interpretable machine learning algorithms mark the dawn of a new postgenomic era of personalised cancer medicine. In Precision Cancer Medicine 2.0, high-resolution personalised clinical decision-making is informed by the comprehensive multiomic profiling of tumour and host, integrated using artificial intelligence.

Keywords: cancer; data integration; machine learning; precision cancer medicine; translational research; tumour biomarkers

DOI: https://doi.org/10.1002/1878-0261.13707

Nat Commun. 2024 Aug 06. 15(1): 6690

DNA methylation and gene expression as determinants of genome-wide cell-free DNA fragmentation.

Michaël Noë, Dimitrios Mathios, Akshaya V Annapragada, Shashikant Koul, Zacharia H Foda, Jamie E Medina, Stephen Cristiano, Christopher Cherry, Daniel C Bruhm, Noushin Niknafs, Vilmos Adleff, Leonardo Ferreira, Hari Easwaran, Stephen Baylin, Jillian Phallen, Robert B Scharpf, Victor E Velculescu.

Circulating cell-free DNA (cfDNA) is emerging as an avenue for cancer detection, but the characteristics of cfDNA fragmentation in the blood are poorly understood. We evaluate the effect of DNA methylation and gene expression on genome-wide cfDNA fragmentation through analysis of 969 individuals. cfDNA fragment ends more frequently contained CCs or CGs, and fragments ending with CGs or CCGs are enriched or depleted, respectively, at methylated CpG positions. Higher levels and larger sizes of cfDNA fragments are associated with CpG methylation and reduced gene expression. These effects are validated in mice with isogenic tumors with or without the mutant IDH1, and are associated with genome-wide changes in cfDNA fragmentation in patients with cancer. Tumor-related hypomethylation and increased gene expression are associated with decrease in cfDNA fragment size that may explain smaller cfDNA fragments in human cancers. These results provide a connection between epigenetic changes and cfDNA fragmentation with implications for disease detection.

DOI: https://doi.org/10.1038/s41467-024-50850-8

Lancet Oncol. 2024 Aug 02. pii: S1470-2045(24)00334-6. [Epub ahead of print]

Atezolizumab and chemotherapy for advanced or recurrent endometrial cancer (AtTEnd): a randomised, double-blind, placebo-controlled, phase 3 trial.

AtTEnd study group

BACKGROUND: At the time of AtTEnd trial design, standard treatment for advanced or recurrent endometrial cancer included carboplatin and paclitaxel chemotherapy. This trial assessed whether combining atezolizumab with chemotherapy might improve outcomes in this population.
METHODS: AtTEnd was a multicentre, double-blind, randomised, placebo-controlled, phase 3 trial done in 89 hospitals in 11 countries across Europe, Australia, New Zealand, and Asia. Enrolled patients were aged 18 years or older, and had advanced or recurrent endometrial carcinoma or carcinosarcoma, an Eastern Cooperative Oncology Group performance status of 0-2, and received no previous systemic chemotherapy for recurrence. Patients were randomly assigned (2:1) using an interactive web response system (block size of six) to either atezolizumab 1200 mg or placebo given intravenously with chemotherapy (carboplatin at area under the curve of 5 or 6 and paclitaxel 175 mg/m2 intravenously on day 1 every 21 days) for 6-8 cycles, then continued until progression. Stratification factors were country, histological subtype, advanced or recurrent status, and mismatch repair (MMR) status. Participants and treating clinicians were masked to group allocation. The hierarchically tested co-primary endpoints were progression-free survival (in patients with MMR-deficient [dMMR] tumours, and in the overall population) and overall survival (in the overall population). Primary analyses were done in the intention-to-treat population, defined as all randomly assigned patients who gave their full consent to participation in the study and data processing. Safety was assessed in all patients included in the intention-to-treat population who received at least one dose of study treatment. Here, we report the primary progression-free survival and the interim overall survival results. This study is ongoing and is registered with ClinicalTrials.gov, NCT03603184.
FINDINGS: Between Oct 3, 2018, and Jan 7, 2022, 551 patients were randomly assigned to atezolizumab (n=362) or placebo (n=189). Two patients in the atezolizumab group were excluded from all analyses due to lack of consent. Median follow-up was 28·3 months (IQR 21·2-37·6). 81 (23%) patients in the atezolizumab group and 44 (23%) patients in the placebo group had dMMR disease by central assessment. In the dMMR population, median progression-free survival was not estimable (95% CI 12·4 months-not estimable [NE]) in the atezolizumab group and 6·9 months (6·3-10·1) in the placebo group (hazard ratio [HR] 0·36, 95% CI 0·23-0·57; p=0·0005). In the overall population, median progression-free survival was 10·1 months (95% CI 9·5-12·3) in the atezolizumab group and 8·9 months (8·1-9·6) in the placebo group (HR 0·74, 95% CI 0·61-0·91; p=0·022). Median overall survival was 38·7 months (95% CI 30·6-NE) in the atezolizumab group and 30·2 months (25·0-37·2) in the placebo group (HR 0·82, 95% CI 0·63-1·07; log-rank p=0·048). The p value for the interim analysis of overall survival did not cross the stopping boundary; therefore, the trial will continue until the required number of events are recorded. The most common grade 3-4 adverse events were neutropenia (97 [27%] of 356 patients in the atezolizumab group vs 51 [28%] of 185 in the placebo group) and anaemia (49 [14%] vs 24 [13%]). Treatment-related serious adverse events occurred in 46 (13%) patients in the atezolizumab group and six (3%) patients in the placebo group. Treatment-related deaths occurred in two patients (pneumonia in one patient in each group).
INTERPRETATION: Atezolizumab plus chemotherapy increased progression-free survival in patients with advanced or recurrent endometrial carcinoma, particularly in those with dMMR carcinomas, suggesting the addition of atezolizumab to standard chemotherapy as first-line treatment in this specific subgroup.
FUNDING: F Hoffmann-La Roche.

DOI: https://doi.org/10.1016/S1470-2045(24)00334-6

Nat Commun. 2024 Aug 06. 15(1): 6684

Robust analysis of allele-specific copy number alterations from scRNA-seq data with XClone.

Rongting Huang, Xianjie Huang, Yin Tong, Helen Y N Yan, Suet Yi Leung, Oliver Stegle, Yuanhua Huang.

Somatic copy number alterations (CNAs) are major mutations that contribute to the development and progression of various cancers. Despite a few computational methods proposed to detect CNAs from single-cell transcriptomic data, the technical sparsity of such data makes it challenging to identify allele-specific CNAs, particularly in complex clonal structures. In this study, we present a statistical method, XClone, that strengthens the signals of read depth and allelic imbalance by effective smoothing on cell neighborhood and gene coordinate graphs to detect haplotype-aware CNAs from scRNA-seq data. By applying XClone to multiple datasets with challenging compositions, we demonstrated its ability to robustly detect different types of allele-specific CNAs and potentially indicate whole genome duplication, therefore enabling the discovery of corresponding subclones and the dissection of their phenotypic impacts.

DOI: https://doi.org/10.1038/s41467-024-51026-0

Ann Oncol. 2024 Jul 09. pii: S0923-7534(24)01011-1. [Epub ahead of print]

ESMO Recommendations on clinical reporting of genomic test results for solid cancers.

BACKGROUND: Genomic tumour profiling has a crucial role in the management of patients with solid cancers, as it helps selecting and prioritising therapeutic interventions based on prognostic and predictive biomarkers, as well as identifying markers of hereditary cancers. Harmonised approaches to interpret the results of genomic testing are needed to support physicians in their decision making, prevent inequalities in precision medicine and maximise patient benefit from available cancer management options.
METHODS: The European Society for Medical Oncology (ESMO) Translational Research and Precision Medicine Working Group assembled a group of international experts to propose recommendations for preparing clinical genomic reports for solid cancers. These recommendations aim to foster best practices in integrating genomic testing within clinical settings. After review of available evidence, several rounds of surveys and focused discussions were conducted to reach consensus on the recommendation statements. Only consensus recommendations were reported. Recommendation statements were graded in two tiers based on their clinical importance: level A (required to maintain common standards in reporting) and level B (optional but necessary to achieve ideal practice).
RESULTS: Genomics reports should present key information in a front page(s) followed by supplementary information in one or more appendices. Reports should be structured into sections: (i) patient and sample details; (ii) assay and data analysis characteristics; (iii) sample-specific assay performance and quality control; (iv) genomic alterations and their functional annotation; (v) clinical actionability assessment and matching to potential therapy indications; and (vi) summary of the main findings. Specific recommendations to prepare each of these sections are made.
CONCLUSIONS: We present a set of recommendations aimed at structuring genomics reports to enhance physician comprehension of genomic profiling results for solid cancers. Communication between ordering physicians and professionals reporting genomic data is key to minimise uncertainties and to optimise the impact of genomic tests in patient care.

Keywords: genomics; next-generation sequencing (NGS); precision medicine; targeted therapies

DOI: https://doi.org/10.1016/j.annonc.2024.06.018