A shared origin from a common ancestor: A case report of two histologically different tumors

The origin of tumors has been under discussion over the years. Different theories have been suggested to explain this phenomenon. Among them, the Cancer-Stem Cells model, is one of the most outstanding. In this study, we reported a case of a 72-year-old man who presented two histologically different tumors with a 7-years gap, a Penile Squamous Cell Carcinoma and a Pleomorphic Undifferentiated Sarcoma, that share some molecular features. Phonotypical differences were showed and confirmed at histological and IHC levels. Molecular analysis showed an HPV infection in the carcinoma. Additionally, sequencing results revealed common (CDKN2A and TERT) and exclusive (FBXW7 and TP53) genetic alterations in both tumors (Table 1). The possible germline origin of common mutations was discarded after negative germline testing. Here we describe, for the first time a clinical case of a possible origin of two histologically different tumors from a common ancestor based on molecular data. Even if different hypothesis appear as possible, the Cancer Stem Cell-based model appears as the most suitable.

Tumor Microenvironment and Its Clinicopathologic and Prognostic Association in Cutaneous and Noncutaneous Angiosarcomas

OBJECTIVES

We explored features of the angiosarcoma (AS) tumor microenvironment to discover subtypes that may respond to immunotherapy.

METHODS

Thirty-two ASs were included. Tumors were studied by histology, immunohistochemistry (IHC), and gene expression profile using the HTG EdgeSeq Precision Immuno-Oncology Assay.

RESULTS

Comparing cutaneous and noncutaneous ASs, the second group showed 155 deregulated genes, and unsupervised hierarchical clustering (UHC) delineated two groups: the first mostly cutaneous AS and the second mainly noncutaneous AS. Cutaneous ASs showed a significantly higher proportion of T cells, natural killer cells, and naive B cells. ASs without MYC amplification revealed a higher immunoscore in comparison with ASs with MYC amplification. PD-L1 was significantly overexpressed in ASs without MYC amplification. UHC showed 135 deregulated genes differentially expressed when comparing ASs from the non-head and neck area with patients who had AS in the head and neck area. ASs from the head and neck area showed high immunoscore. PD1/PD-L1 content was significantly more highly expressed in ASs from the head and neck area. IHC and HTG gene expression profiling revealed a significant correlation between PD1, CD8, and CD20 protein expression but not PD-L1.

CONCLUSIONS

Our HTG analyses confirmed a high degree of tumor and microenvironment heterogeneity. Cutaneous ASs, ASs without MYC amplification, and ASs located in the head and neck area seem to be the most immunogenic subtypes in our series.

The Scarface Score: Deciphering Response to DNA Damage Agents in High-Grade Serous Ovarian Cancer-A GEICO Study

Genomic Instability (GI) is a transversal phenomenon shared by several tumor types that provide both prognostic and predictive information. In the context of high-grade serous ovarian cancer (HGSOC), response to DNA-damaging agents such as platinum-based and poly(ADP-ribose) polymerase inhibitors (PARPi) has been closely linked to deficiencies in the DNA repair machinery by homologous recombination repair (HRR) and GI. In this study, we have developed the Scarface score, an integrative algorithm based on genomic and transcriptomic data obtained from the NGS analysis of a prospective GEICO cohort of 190 formalin-fixed paraffin-embedded (FFPE) tumor samples from patients diagnosed with HGSOC with a median follow up of 31.03 months (5.87-159.27 months). In the first step, three single-source models, including the SNP-based model (accuracy = 0.8077), analyzing 8 SNPs distributed along the genome; the GI-based model (accuracy = 0.9038) interrogating 28 parameters of GI; and the HTG-based model (accuracy = 0.8077), evaluating the expression of 7 genes related with tumor biology; were proved to predict response. Then, an ensemble model called the Scarface score was found to predict response to DNA-damaging agents with an accuracy of 0.9615 and a kappa index of 0.9128 (p < 0.0001). The Scarface Score approaches the routine establishment of GI in the clinical setting, enabling its incorporation as a predictive and prognostic tool in the management of HGSOC.

Prognostic Impact of let-7e MicroRNA and Its Target Genes in Localized High-Risk Intestinal GIST: A Spanish Group for Research on Sarcoma (GEIS) Study

MicroRNAs (miRNAs) are small non-coding RNAs that negatively regulate gene expression at the post-transcriptional level, and they have been described as being associated with tumor prognosis. Here, miRNA profiling was planned to explore new molecular prognostic biomarkers in localized intestinal high-risk GIST. Paraffin tumor blocks of 14 and 86 patients were used in the discovery and expansion sets, respectively. GeneChip miRNA v3.0 was employed to identify the miRNAs differentially expressed between relapsed and non-relapsed patient samples, which were validated in the expansion set, by qRT-PCR. RT2 Profiler PCR Array was used for the screening of let-7e targets. Expression levels were correlated with relapse-free survival and overall survival. In the discovery set, 39 miRNAs were significantly deregulated, let-7e and miR-550 being the most underexpressed and overexpressed miRNAs in the relapsed group, respectively. In the expansion set, the underexpression of let-7e or the overexpression of 4 of its target genes (ACVR1B, CASP3, COL3A1, and COL5A2) were statistically associated with worse relapse-free survival. The expression of let-7e and 4 of its target genes are potential prognostic biomarkers in high-risk localized intestinal GIST. The expression of these genes is a potential molecular tool useful for a more accurate prognosis in this subset of GIST patients.

Prognostic classification of endometrial cancer using a molecular approach based on a twelve-gene NGS panel

Endometrial Cancer (EC) is one of the most common malignancies in women in developed countries. Molecular characterization of different biotypes may improve clinical management of EC. The Cancer Genome Atlas (TCGA) project has revealed four prognostic EC subgroups: POLE, MSI; Copy Number Low (CNL) and Copy Number High (CNH). The goal of this study was to develop a method to classify tumors in any of the four EC prognostic groups using affordable molecular techniques. Ninety-six Formalin-Fixed Paraffin-embedded (FFPE) samples were sequenced following a NGS TruSeq Custom Amplicon low input (Illumina) protocol interrogating a multi-gene panel. MSI analysis was performed by fragment analysis using eight specific microsatellite markers. A Random Forest classification algorithm (RFA), considering NGS results, was developed to stratify EC patients into different prognostic groups. Our approach correctly classifies the EC patients into the four TCGA prognostic biotypes. The RFA assigned the samples to the CNH and CNL groups with an accuracy of 0.9753 (p < 0.001). The prognostic value of these groups was prospectively reproduced on our series both for Disease-Free Survival (p = 0.004) and Overall Survival (p = 0.030).Hence, with the molecular approach herein described, a precise and suitable tool that mimics the prognostic EC subtypes has been solved and validated. Procedure that might be introduced into routine diagnostic practices.

Differential copy number alteration profiles among gynecological malignancies

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Background: Copy number alterations (CNA) constitutes a genomic hallmark that defines specific outcomes in gynecological neoplasms, as evidenced by the integrated analysis of the high-grade serous ovarian carcinoma (HGSOC) and endometrial carcinomas (EC) performed by the TCGA Consortium. The purpose of this study is to set up an NGS-based technology to obtain CNA profiles on formalin-fixed paraffin-embedded (FFPE) samples with clinical utility. Methods: FFPE blocks from 14 EC and 12 HGSOC were analyzed using a SureSelectXT custom panel plus OneSeq backbone, interrogating 147.000 SNPs (Agilent). CNA groups were defined in EC with a RF algorithm based on genotyping data as previously reported (Romero, ASCO 2018) and in HGSOC Homologous recombination deficiency (HRD) was determined by sequencing a serie of 35 HR genes. saasCNV pipeline was used to perform CNA calling. Results: Ten (38.50 %) of our cases were classified as CN Low (CNL), 8 as CN high (CNH)-RF (30.75 %) and 8 CNH-HRD (30.75 %). CNL profiles from EC and OC are homogenous in terms of genomic stability. CNH-RF and CNH-HRD cases harbor the highest percentage of genomic instability (p = 0.012) with distinct patterns of CNA. CNH-HRD is characterized by a higher ratio of genomic losses (p = 0.023). However, CNH-RF is mainly defined by gains (p = 0.011) (Table). Conclusions: Our NGS-based approach represents a FFPE clinically available procedure to define CNA alterations in gynecological cancer with distinct CNH patterns with prognostic potential.[Table: see text]