bims-tumhet Biomed News
on Tumor Heterogeneity
Issue of 2024‒04‒21
nine papers selected by
Sergio Marchini, Humanitas Research

  1. Gynecol Oncol. 2024 Apr 18. pii: S0090-8258(24)00192-6. [Epub ahead of print]186 110-116
      OBJECTIVE: Recent evidence suggests that the fimbriated end of the fallopian tube harbors the precursor cells for many high-grade ovarian cancers, opening the door for development of better screening methods that directly assess the fallopian tube in women at risk for malignancy. Previously we have shown that the karyometric signature is abnormal in the fallopian tube epithelium in women at hereditary risk of ovarian cancer. In this study, we sought to determine whether the karyometric signature in serous tubal intraepithelial carcinoma (STIC) is significantly different from normal, and whether an abnormal karyometric signature can be detected in histologically normal tubal epithelial cells adjacent to STIC lesions.METHODS: The karyometric signature was measured in epithelial cells from the proximal and fimbriated portion of the fallopian tube in fallopian tube specimens removed from women at: 1) average risk for ovarian cancer undergoing surgery for benign gynecologic indications (n = 37), 2) hereditary risk of ovarian cancer (germline BRCA alterations) undergoing risk-reducing surgery (n = 44), and 3) diagnosed with fimbrial STICs (n = 17).
    RESULTS: The karyometric signature in tubes with fimbrial STICs differed from that of tubes with benign histology. The degree of karyometric alteration increased with increasing proximity to fimbrial STICs, ranging from moderate in the proximal portion of the tube, to greatest in both normal appearing fimbrial cells near STICs as well as in fimbrial STIC lesions.
    CONCLUSION: These data demonstrate an abnormal karyometric signature in STICs that may extend beyond the STIC, potentially providing an opportunity for early detection of fallopian tube neoplasia.
    Keywords:  Early detection; Fallopian tube cancer; Karyometry; Ovarian cancer; Screening
  2. Sci Adv. 2024 Apr 19. 10(16): eadk8805
      High-grade serous ovarian carcinoma (HGSOC), the deadliest form of ovarian cancer, is typically diagnosed after it has metastasized and often relapses after standard-of-care platinum-based chemotherapy, likely due to advanced tumor stage, heterogeneity, and immune evasion and tumor-promoting signaling from the tumor microenvironment. To understand how spatial heterogeneity contributes to HGSOC progression and early relapse, we profiled an HGSOC tissue microarray of patient-matched longitudinal samples from 42 patients. We found spatial patterns associated with early relapse, including changes in T cell localization, malformed tertiary lymphoid structure (TLS)-like aggregates, and increased podoplanin-positive cancer-associated fibroblasts (CAFs). Using spatial features to compartmentalize the tissue, we found that plasma cells distribute in two different compartments associated with TLS-like aggregates and CAFs, and these distinct microenvironments may account for the conflicting reports about the role of plasma cells in HGSOC prognosis.
  3. Gynecol Oncol. 2024 Apr 13. pii: S0090-8258(24)00193-8. [Epub ahead of print]186 94-103
      The Cancer Genome Atlas (TCGA) Research Network described 4 molecular subgroups of endometrial carcinomas with different outcome: 1) POLE ultramutated endometrioid carcinomas which have an indolent behavior; 2) microsatellite instability hypermutated endometrioid carcinomas associated with intermediate prognosis; 3) copy-number low endometrioid carcinomas also with intermediate prognosis; and 4) copy-number high predominantly serous (non-endometrioid) but also serous-like endometrioid carcinomas, almost always carrying TP53 mutations, with poor clinical outcome. After 10 years of comprehensive analysis, it appears that the only real contribution of TCGA to the clinical management of these patients would be limited to the infrequent high-grade, early-stage endometrioid carcinomas with POLE exonuclease domain mutations, as these patients could benefit from a de-escalating treatment; knowledge about the other three subgroups has not changed significantly. The copy-number low (or non-specific genetic profile) which is the most frequent subgroup, is a mixture subgroup where investigators are currently trying to establish prognostic markers; for example, unexpected variations in a relatively small percentage of cases (i.e., CTNNB1 mutated or p53 aberrant low-grade and low-stage endometrioid carcinomas associated with unfavorable prognosis). On the other hand, TCGA has underlined that a small number of grade 3 endometrioid carcinomas, all TP53 mutated, overlap with copy-number high serous carcinomas. Recently, TCGA molecular subgroups have been integrated into the 2023 International Federation of Gynecology and Obstetrics (FIGO) staging classification which incorporates other non-anatomic parameters like histotype, tumor grade, and lymphovascular space invasion. The result is a complicated and non-intuitive classification that makes its clinical application difficult and does not facilitate correspondence with the 2009 FIGO staging.
    Keywords:  Endometrial carcinoma; FIGO staging classification; POLE; TCGA
  4. Cold Spring Harb Perspect Med. 2024 Apr 15. pii: a041336. [Epub ahead of print]
      Despite progress in other tumor types, immunotherapy is not yet part of the standard of care treatment for high-grade serous ovarian cancer patients. Although tumor infiltration by T cells is frequently observed in patients with ovarian cancer, clinical responses to immunotherapy remain low. Mechanisms for immune resistance in ovarian cancer have been explored and may provide insight into future approaches to improve response to immunotherapy agents. In this review, we discuss what is known about the immune landscape in ovarian cancer, review the available data for immunotherapy-based strategies in these patients, and provide possible future directions.
  5. bioRxiv. 2024 Apr 03. pii: 2024.04.03.587939. [Epub ahead of print]
      Cancer development is characterized by chromosomal instability, manifesting in frequent occurrences of different genomic alteration mechanisms ranging in extent and impact. Mathematical modeling can help evaluate the role of each mutational process during tumor progression, however existing frameworks can only capture certain aspects of chromosomal instability (CIN). We present CINner, a mathematical framework for modeling genomic diversity and selection during tumor evolution. The main advantage of CINner is its flexibility to incorporate many genomic events that directly impact cellular fitness, from driver gene mutations to copy number alterations (CNAs), including focal amplifications and deletions, missegregations and whole-genome duplication (WGD). We apply CINner to find chromosome-arm selection parameters that drive tumorigenesis in the absence of WGD in chromosomally stable cancer types. We found that the selection parameters predict WGD prevalence among different chromosomally unstable tumors, hinting that the selective advantage of WGD cells hinges on their tolerance for aneuploidy and escape from nullisomy. Direct application of CINner to model the WGD proportion and fraction of genome altered (FGA) further uncovers the increase in CNA probabilities associated with WGD in each cancer type. CINner can also be utilized to study chromosomally stable cancer types, by applying a selection model based on driver gene mutations and focal amplifications or deletions. Finally, we used CINner to analyze the impact of CNA probabilities, chromosome selection parameters, tumor growth dynamics and population size on cancer fitness and heterogeneity. We expect that CINner will provide a powerful modeling tool for the oncology community to quantify the impact of newly uncovered genomic alteration mechanisms on shaping tumor progression and adaptation.
  6. Genome Biol. 2024 Apr 18. 25(1): 99
      Spatial molecular data has transformed the study of disease microenvironments, though, larger datasets pose an analytics challenge prompting the direct adoption of single-cell RNA-sequencing tools including normalization methods. Here, we demonstrate that library size is associated with tissue structure and that normalizing these effects out using commonly applied scRNA-seq normalization methods will negatively affect spatial domain identification. Spatial data should not be specifically corrected for library size prior to analysis, and algorithms designed for scRNA-seq data should be adopted with caution.
  7. Methods Mol Biol. 2024 ;2794 293-304
      Droplet digital PCR (ddPCR) is an emerging method for the absolute quantification of PCR products, and it can detect DNA copy numbers accurately. It analyzes the end-point absolute fluorescence signals of the PCR-positive droplets and calculates the target concentration. EvaGreen is a nonspecific double-stranded DNA-binding fluorescent dye, and the ddPCR system also supports assays using this cost-effective hydrolysis probe. Here, we describe a simple method of quantification for DNA copy numbers using the EvaGreen single-color fluorescent design.
    Keywords:  DNA copy numbers; Droplet digital PCR; EvaGreen; QuantaSoft software; Single color; ddPCR
  8. Cell Mol Life Sci. 2024 Apr 17. 81(1): 185
      When cells proliferate, stress on DNA replication or exposure to endogenous or external insults frequently results in DNA damage. DNA-Damage Response (DDR) networks are complex signaling pathways used by multicellular organisms to prevent DNA damage. Depending on the type of broken DNA, the various pathways, Base-Excision Repair (BER), Nucleotide Excision Repair (NER), Mismatch Repair (MMR), Homologous Recombination (HR), Non-Homologous End-Joining (NHEJ), Interstrand Crosslink (ICL) repair, and other direct repair pathways, can be activated separately or in combination to repair DNA damage. To preserve homeostasis, innate and adaptive immune responses are effective defenses against endogenous mutation or invasion by external pathogens. It is interesting to note that new research keeps showing how closely DDR components and the immune system are related. DDR and immunological response are linked by immune effectors such as the cyclic GMP-AMP synthase (cGAS)-Stimulator of Interferon Genes (STING) pathway. These effectors act as sensors of DNA damage-caused immune response. Furthermore, DDR components themselves function in immune responses to trigger the generation of inflammatory cytokines in a cascade or even trigger programmed cell death. Defective DDR components are known to disrupt genomic stability and compromise immunological responses, aggravating immune imbalance and leading to serious diseases such as cancer and autoimmune disorders. This study examines the most recent developments in the interaction between DDR elements and immunological responses. The DDR network's immune modulators' dual roles may offer new perspectives on treating infectious disorders linked to DNA damage, including cancer, and on the development of target immunotherapy.
    Keywords:  Adaptive immunity; DNA-damage response (DDR); IFN; Innate immunity; cGAS–STING
  9. Immunology. 2024 Apr 15.
      Despite progress in cancer immunotherapy, ovarian cancer (OC) prognosis continues to be disappointing. Recent studies have shed light on how not just tumour cells, but also the complex tumour microenvironment, contribute to this unfavourable outcome of OC immunotherapy. The complexities of the immune microenvironment categorize OC as a 'cold tumour'. Nonetheless, understanding the precise mechanisms through which the microenvironment influences the effectiveness of OC immunotherapy remains an ongoing scientific endeavour. This review primarily aims to dissect the inherent characteristics and behaviours of diverse cells within the immune microenvironment, along with an exploration into its reprogramming and metabolic changes. It is expected that these insights will elucidate the operational dynamics of the immune microenvironment in OC and lay a theoretical groundwork for improving the efficacy of immunotherapy in OC management.
    Keywords:  drug resistance; immunotherapy; ovarian cancer; targeted therapy; tumour immune microenvironment