bims-tumhet Biomed News
on Tumor Heterogeneity
Issue of 2021‒06‒27
six papers selected by
Sergio Marchini
Humanitas Research

  1. Adv Cancer Res. 2021 ;pii: S0065-230X(21)00022-1. [Epub ahead of print]151 425-468
      Colorectal cancer is a leading cause of cancer related deaths worldwide. One of the hallmarks of cancer and a fundamental trait of virtually all gastrointestinal cancers is genomic and epigenomic DNA alterations. Cancer cells acquire genetic and epigenetic alterations that drive the initiation and progression of the cancers by altering the molecular and cell biological process of the cells. These alterations, as well as other host and microenvironment factors, ultimately mediate the initiation and progression of cancers, including colorectal cancer. Epigenetic alterations, which include changes affecting DNA methylation, histone modifications, chromatin structure, and noncoding RNA expression, have emerged as a major class of molecular alteration in colon polyps and colorectal cancer. The classes of epigenetic alterations, their status in colorectal polyps and cancer, their effects on neoplasm biology, and their application to clinical care will be discussed.
    Keywords:  Biomarkers; Chromatin; Colon polyps; Colorectal cancer; DNA methylation; Diagnosis; Histone; Noncoding RNA; Predictive; Prognosis; Treatment
  2. Mol Cancer Ther. 2021 Jun 25. pii: molcanther.0992.2020. [Epub ahead of print]
      Ovarian cancer is the second most common gynecologic malignancy in the United States (US) and the most common cause of gynecologic cancer-related death. The majority of ovarian cancers ultimately recur despite excellent response rates to upfront platinum and taxane-based chemotherapy. Maintenance therapy after frontline treatment has emerged in recent years as an effective tool for extending the platinum-free interval of these patients. Maintenance therapy with poly (ADP-ribose) polymerase inhibitors (PARPi) in particular has become part of standard of care in the upfront setting and in patients with platinum-sensitive disease. HR deficient (HRD) tumors have a nonfunctioning homologous recombination repair (HRR) pathway and respond well to PARPi, which takes advantage of synthetic lethality by concomitantly impairing DNA repair mechanisms. Conversely, patients with a functioning HRR pathway, i.e. HR proficient (HRP) tumors, can still elicit benefit from PARPi, but the efficacy is not as remarkable as what is seen in HRD tumors. PARPi are ineffective in some patients due to HR proficiency, which is either inherent to the tumor or potentially acquired as a method of therapeutic resistance. This review seeks to outline current strategies employed by clinicians and scientists to overcome PARPi resistance - either acquired or inherent to the tumor.
  3. BMC Med Genomics. 2021 Jun 19. 14(1): 163
      BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common and invasive malignant tumors in the world. The change in DNA methylation is a key event in HCC.METHODS: Methylation datasets for HCC and 17 other types of cancer were downloaded from The Cancer Genome Atlas (TCGA). The CpG sites with large differences in methylation between tumor tissues and paracancerous tissues were identified. We used the HCC methylation dataset downloaded from the TCGA as the training set and removed the overlapping sites among all cancer datasets to ensure that only CpG sites specific to HCC remained. Logistic regression analysis was performed to select specific biomarkers that can be used to diagnose HCC, and two datasets-GSE157341 and GSE54503-downloaded from GEO as validation sets were used to validate our model. We also used a Cox regression model to select CpG sites related to patient prognosis.
    RESULTS: We identified 6 HCC-specific methylated CpG sites as biomarkers for HCC diagnosis. In the training set, the area under the receiver operating characteristic (ROC) curve (AUC) for the model containing all these sites was 0.971. The AUCs were 0.8802 and 0.9711 for the two validation sets from the GEO database. In addition, 3 other CpG sites were analyzed and used to create a risk scoring model for patient prognosis and survival prediction.
    CONCLUSIONS: Through the analysis of HCC methylation datasets from the TCGA and Gene Expression Omnibus (GEO) databases, potential biomarkers for HCC diagnosis and prognosis evaluation were ascertained.
  4. Epigenetics Chromatin. 2021 Jun 19. 14(1): 28
      BACKGROUND: With rapidly dropping sequencing cost, the popularity of whole-genome DNA methylation sequencing has been on the rise. Multiple library preparation protocols currently exist. We have performed 22 whole-genome DNA methylation sequencing experiments on snap frozen human samples, and extensively benchmarked common library preparation protocols for whole-genome DNA methylation sequencing, including three traditional bisulfite-based protocols and a new enzyme-based protocol. In addition, different input DNA quantities were compared for two kits compatible with a reduced starting quantity. In addition, we also present bioinformatic analysis pipelines for sequencing data from each of these library types.RESULTS: An assortment of metrics were collected for each kit, including raw read statistics, library quality and uniformity metrics, cytosine retention, and CpG beta value consistency between technical replicates. Overall, the NEBNext Enzymatic Methyl-seq and Swift Accel-NGS Methyl-Seq kits performed quantitatively better than the other two protocols. In addition, the NEB and Swift kits performed well at low-input amounts, validating their utility in applications where DNA is the limiting factor.
    RESULTS: The NEBNext Enzymatic Methyl-seq kit appeared to be the best option for whole-genome DNA methylation sequencing of high-quality DNA, closely followed by the Swift kit, which potentially works better for degraded samples. Further, a general bioinformatic pipeline is applicable across the four protocols, with the exception of extra trimming needed for the Swift Biosciences's Accel-NGS Methyl-Seq protocol to remove the Adaptase sequence.
    Keywords:  DNA methylation; Enzymatic methylation sequencing; Epigenetics; Fallopian tube; Whole-genome bisulfite sequencing
  5. Hum Pathol. 2021 Jun 18. pii: S0046-8177(21)00110-6. [Epub ahead of print]
      Molecular findings in ovarian, fallopian tube, and peritoneal high-grade serous carcinoma (HGSCa) are emerging as potential prognostic indicators. The chemotherapy response score (CRS) has been proposed as a histologic based prognostic factor in patients with HGSCa treated with neoadjuvant chemotherapy (NACT). No study details the relationship between the mutational landscape of HGSCa and the CRS. This study addresses this issue using Next-Generation Sequencing (NGS).We retrospectively identified 25 HGSCas treated with NACT and pathology material available to calculate the CRS. All cases had NGS on the primary debulking specimen post-NACT. The 3-tier Böhm CRS was applied to the omentum, adnexa and calculated as a combined score. Tumor mutation burden (TMB) and TP53 variant allele frequency (VAF) were calculated and used in correlative analysis. All cases had at least 1 mutation, most commonly TP53 (25 cases, 100%). Other mutations were: BRCA2 (1 case, 4%), ARID1A (2 cases, 8%), and 1 (4%) of each of the following: ERBB2, NTRK3, STK11, NTRK2, TSC1, PIK3CA, NF1, NOTCH3, CDK2, SMAD4 and PMS2. TMB ranged from 2.58 to 7.75 (median 3.84). There was no statistically significant relationship between the TMB and omental CRS, R-squared = 0.011 (p=0.62); adnexal CRS, R-squared = 0.005 (p=0.74); or with the combined CRS, R-squared = 0.009 (p=0.65). Statistically significant correlation was found between the TP53 VAF and the omental CRS (R-squared = 0.28, p=0.007), adnexal CRS (R-squared = 0.26, p=0.01), and the combined CRS (R-squared = 0.33, p=0.0026). The TP53 VAF was adjusted for percent of tumor present on the slide resulting in an average per cell TP53 mutational load, resulting in similar results with a statistically significant correlation between the average per cell TP53 mutational load and the omental CRS (R-squared = 0.27, p=0.02), adnexal CRS (R-squared = 0.16, p=0.05) and the combined CRS (R-squared = 0.23, p=0.02).In summary, NGS confirmed TP53 mutations in all cases of HGSCa. TMB showed no correlation with the CRS. TP53 VAF and average per cell TP53 mutational load showed significant correlation with the CRS, whether graded on the adnexa, omentum or as a combined score, indicating concordance between molecular and histological findings following NACT.
    Keywords:  TP53; chemotherapy response; fallopian tube; high-grade serous carcinoma; mutational landscape; neoadjuvant chemotherapy; ovarian; peritoneal; tumor mutation burden
  6. Front Oncol. 2021 ;11 668151
      Ovarian cancer is one of the most common gynecologic cancers that has the highest mortality rate. Endometrioid ovarian cancer, a distinct subtype of epithelial ovarian cancer, is associated with endometriosis and Lynch syndrome, and is often accompanied by synchronous endometrial carcinoma. In recent years, dysbiosis of the microbiota within the female reproductive tract has been suggested to be involved in the pathogenesis of endometrial cancer and ovarian cancer, with some specific pathogens exhibiting oncogenic having been found to contribute to cancer development. It has been shown that dysregulation of the microenvironment and accumulation of mutations are stimulatory factors in the progression of endometrioid ovarian carcinoma. This would be a potential therapeutic target in the future. Simultaneously, multiple studies have demonstrated the role of four molecular subtypes of endometrioid ovarian cancer, which are of particular importance in the prediction of prognosis. This literature review aims to compile the potential mechanisms of endometrioid ovarian cancer, molecular characteristics, and molecular pathological types that could potentially play a role in the prediction of prognosis, and the novel therapeutic strategies, providing some guidance for the stratified management of ovarian cancer.
    Keywords:  endometrioid ovarian cancer; microbiota dysbiosis; molecular characteristic; molecular subtypes; prognosis; treatment strategy