Serum IgG4 Concentration is a Potential Predictive Biomarker in Glucocorticoid Treatment for Idiopathic Retroperitoneal Fibrosis

Objectives: To evaluate the management and outcome of idiopathic retroperitoneal fibrosis (iRPF) in Japan, and identify its clinical biomarker. Methods: We retrospectively analyzed 129 patients with iRPF treated between January 2008 and May 2018 at 12 university and related hospitals. Patients treated with glucocorticoid were analyzed to identify a predictive biomarker. These patients were classified into three groups according to overall effectiveness (no change: NC, complete response: CR and partial response groups: PR), and each parameter was compared statistically.Results: Male-female ratio was 5: 1, and median age at diagnosis was 69 (33-86) years. Smoking history was reported in 59.6% of the patients. As treatment, 95 patients received glucocorticoid therapy with an overall response rate of 84%. As a result, serum concentration of IgG4 was significantly decreased in NC group compared with the other two groups (56.6mg/dL vs 255mg/dL, 206mg/dL, P=0.0059 and 0.0078). ROC analysis was performed between the non-responder (NC) and responder groups (CR+PR) to identify the cut-off value of serum IgG4 as a predictive marker. As a result, AUC was 0.793 and the values of sensitivity and specificity were 0.85 and 0.64, respectively, under the cut-off values of 67.6mg/dL. Conclusions: In the majority of iRPF patients, glucocorticoid therapy resulted in a favorable response. Pre-treatment serum IgG4 concentration may have potential as a predictive biomarker of steroid treatment.

Interferon-Stimulated Exonuclease Gene 20 is A Prognosis and Predictive Biomarker and Correlated with Macrophages M2 Polarization in Glioblastoma: A Pan-Cancer Analysis

Background: Since the mutation of isocitrate dehydrogenase 1 was confirmed to be different in the tumor microenvironment of multiple cancer types, several researchers have included it in the study of tumor-infiltrating immune cells. Interferon-stimulated exonuclease gene 20 (ISG20) plays a role in the modulation of immunity and inflammation, and its abnormally high expression is conducive for the progression of tumor malignancy. However, whether ISG20 is associated with isocitrate dehydrogenase 1 mutation during tumorigenesis and cancer progression remains unknown to date. Methods: TIMER2.0, ONCOMINE, GEPIA2, TCGA and CGGA were applied to assess the clinical significance of ISG20 and its correlation with tumor-infiltrating immune cells in glioma. cBioPortal and MethSurv databases were used to observe the genetic and DNA methylation changes of ISG20, respectively. Visualization of data was mostly achieved by R language. Quantitative real-time PCR (qRT-PCR) and Immunohistochemistry (IHC) was performed to evaluate the mRNA and protein expression.Results: ISG20 expression was significantly different in most cancers. However, when we combined ISG20 with isocitrate dehydrogenase 1 mutation, we found significant differences only in glioblastoma (GBM). The clinical values of ISG20 in glioblastoma showed that the ISG20 overexpression was strongly associated with a worse overall survival (OS). Additionally, ISG20 was altered in 9% of samples of patients with GBM, and ISG20 expression was negatively correlated with its DNA methylation level. More importantly, ISG20 expression was associated with macrophage alternatively activated (M2) polarization in glioblastoma. Conclusions: ISG20 overexpression is conducive to malignant phenotype but adverse to OS, suggesting that ISG20 is a potential therapeutic target and prognosis and predictive biomarker in patients with GBM.

Tissue Microarray from Cell Block Material (cbTMA)—An Additional Shot for Cytology in the Predictive Pathology Era: The PD-L1 Experience

Generally, predictive biomarker tests are clinically validated on histological formalin-fixed, paraffin-embedded (FFPE) samples. In addition to FFPE samples, cytological samples have also emerged as a useful approach to detect predictive biomarkers. However, as of today, despite the promising results reported in the recent literature, their full implementation in routine clinical practice is still lagging owing to a lack of standardized preparatory protocols, challenging assessments of cyto-histological correlation, and variable inter-observer agreement. The aim of this report was to explore the possibility of implementing a large-scale validation of predictive biomarker testing on cytological material. To this aim, we evaluated the technical feasibility of PD-L1 assessment on a cell block (CB)-derived tissue microarray (cbTMA). Consecutive and unselected CBs prepared from metastatic lymph node fine-needle cytology (FNC) samples were retrospectively collected and used for TMA construction. PD-L1 immunohistochemistry (IHC) was carried out on cbTMA sections with the companion diagnostic kit SP263 assay. TMA contained 33 CB-derived cores. A total of 20 sections were hematoxylin and eosin (H&E) stained. Overall, 29 (88%) samples were visible at least in one H&E-stained slide. Four cases out of five sections stained with the SP263 assay (4/29, 13.8%) showed PD-L1 positivity in neoplastic and/or immune cells; remarkably, no unspecific background was observed. Although our study was based on a limited and non-selected series, our findings do provide proof of concept for the use of cbTMA in predictive biomarker testing on cytological material in large-scale post-clinical trial validation studies, multicenter studies, and quality control programs.

Modulation of DNA Damage Response by SAM and HD Domain Containing Deoxynucleoside Triphosphate Triphosphohydrolase (SAMHD1) Determines Prognosis and Treatment Efficacy in Different Solid Tumor Types

SAMHD1 is a deoxynucleotide triphosphate (dNTP) triphosphohydrolase with important roles in the control of cell proliferation and apoptosis, either through the regulation of intracellular dNTPs levels or the modulation of the DNA damage response. However, SAMHD1 role in cancer evolution is still unknown. We performed the first in-depth study of SAMHD1 role in advanced solid tumors, by analyzing samples of 128 patients treated with chemotherapy agents based on platinum derivatives and/or antimetabolites and developing novel in vitro knock-out models to explore the mechanisms driving SAMHD1 function in cancer. Low or no expression of SAMHD1 was associated with a positive prognosis in breast, ovarian and non-small cell lung cancer (NSCLC) cancer patients. A predictive value was associated to low-SAMHD1 expression in NSCLC and ovarian patients treated with antimetabolites in combination with platinum derivatives. In vitro, SAMHD1 knock-out cells showed increased γ-H2AX and apoptosis suggesting that SAMHD1 depletion induces DNA damage leading to cell death. In vitro treatment with platinum-derived drugs significantly enhanced γ-H2AX and apoptotic markers expression in knock-out cells, indicating a synergic effect of SAMHD1 depletion and platinum-based treatment. SAMHD1 expression represents a new strong prognostic and predictive biomarker in solid tumors and thus, modulation of SAMHD1 function may constitute a promising target for the improvement of cancer therapy.

Immune Effective Score as a Predictor of Response to Neoadjuvant Trastuzumab Therapy and a Prognostic Indicator for HER2-Positive Breast Cancer

Background: HER2-positive breast cancer (BC) is a highly aggressive phenotype. The role of the host immune features in predictive response to anti-HER2 therapies and prognosis in BC has already been suggested. We aimed to develop a predictive and prognostic model and examine its relevance to the clinical outcomes of patients with HER2-positive BC. Methods: Immune effective score (IES) was constructed using principal component analysis algorithms. A bioinformatic analysis using four independent cohorts (GSE66305, n = 88; GSE130786, n = 110; TCGA, n = 123; METABRIC, n = 236) established associations between IES and clinical outcomes. Results: Genes associated with neoadjuvant trastuzumab therapy response were enriched in pathways related to antitumor immune activities. IES was demonstrated to be a predictive biomarker to neoadjuvant trastuzumab therapy benefits (GSE66305: area under the curve (AUC) = 0.804; GSE130786: AUC = 0.704). In addition, IES was identified as an independent prognostic factor for overall survival (OS) in the TCGA cohort (p = 0.036, hazard ratio (HR): 0.66, 95% confidence interval (CI): 0.449–0.97) and METABRIC cohort (p = 0.037, HR: 0.9, 95% CI: 0.81–0.99). Conclusion: IES has a predictive value for response to neoadjuvant trastuzumab therapy and independent prognostic value for HER2-positive breast cancer.

Circulating Tumor Cell Transcriptomics as Biopsy Surrogates in Metastatic Breast Cancer

Background Metastatic breast cancer (MBC) and the circulating tumor cells (CTCs) leading to macrometastases are inherently different than primary breast cancer. We evaluated whether whole transcriptome RNA-Seq of CTCs isolated via an epitope-independent approach may serve as a surrogate for biopsies of macrometastases. Methods We performed RNA-Seq on fresh metastatic tumor biopsies, CTCs, and peripheral blood (PB) from 19 newly diagnosed MBC patients. CTCs were harvested using the ANGLE Parsortix microfluidics system to isolate cells based on size and deformability, independent of a priori knowledge of cell surface marker expression. Results Gene expression separated CTCs, metastatic biopsies, and PB into distinct groups despite heterogeneity between patients and sample types. CTCs showed higher expression of immune oncology targets compared with corresponding metastases and PB. Predictive biomarker (n = 64) expression was highly concordant for CTCs and metastases. Repeat observation data post-treatment demonstrated changes in the activation of different biological pathways. Somatic single nucleotide variant analysis showed increasing mutational complexity over time. Conclusion We demonstrate that RNA-Seq of CTCs could serve as a surrogate biomarker for breast cancer macrometastasis and yield clinically relevant insights into disease biology and clinically actionable targets. Visual Abstract Primary tumor cells (left side) disseminate via the blood stream to seed distant metastases (right side). Peripheral blood can be used for enrichment of CTCs (potentially representative of the full heterogeneity of a patient’s cancer) as a liquid biopsy. RNA-Seq can identify predictive biomarker expression in enriched CTCs as a surrogate for macrometastatic tissue biopsies. Different colored circles represent different cancer cell clones, representing heterogeneity in the primary tumor, and increased heterogeneity in metastatic tumors.

Programmed Death-Ligand 1 (PD-L1) as Immunotherapy Biomarker in Breast Cancer

Breast cancer constitutes the most common malignant neoplasm in women around the world. Approximately 12% of patients are diagnosed with metastatic stage, and between 5 and 30% of early or locally advanced BC patients will relapse, making it an incurable disease. PD-L1 ligation is an immune inhibitory molecule of the activation of T cells, playing a relevant role in numerous types of malignant tumors, including BC. The objective of the present review is to analyze the role of PD-L1 as a biomarker in the different BC subtypes, adding clinical trials with immune checkpoint inhibitors and their applicable results. Diverse trials using immunotherapy with anti-PD-1/PD-L1 in BC, as well as prospective or retrospective cohort studies about PD-L1 in BC, were included. Despite divergent results in the reviewed studies, PD-L1 seems to be correlated with worse prognosis in the hormone receptor positive subtype. Immune checkpoints inhibitors targeting the PD-1/PD-L1 axis have achieved great response rates in TNBC patients, especially in combination with chemotherapy, making immunotherapy a new treatment option in this scenario. However, the utility of PD-L1 as a predictive biomarker in the rest of BC subtypes remains unclear. In addition, predictive differences have been found in response to immunotherapy depending on the stage of the tumor disease. Therefore, a better understanding of tumor microenvironment, as well as identifying new potential biomarkers or combined index scores, is necessary in order to make a better selection of the subgroups of BC patients who will derive benefit from immune checkpoint inhibitors.

Homologous Recombination Deficiency Associated With Response to Poly (ADP-Ribose) Polymerase Inhibitors in Ovarian Cancer Patients: The First Real-Word Evidence From China

Homologous recombination deficiency (HRD) is an approved predictive biomarker for Poly (ADP-ribose) polymerase inhibitors (PARPi) in ovarian cancer. However, the proportion of positive HRD in the real world and the relationship between HRD status and PARPi in Chinese ovarian cancer patients remain unknown. A total of 67 ovarian cancer patients who underwent PARPi, either olaparib or niraparib, were enrolled and passed inclusion criteria from August 2018 to January 2021 in the Affiliated Cancer Hospital of Nanjing Medical University. HRD status correlation with Progression-free survival (PFS) was analyzed and summarized with a log-rank test. Univariate and multiple cox-regression analyses were conducted to investigate all correlated clinical factors. Approximately 68.7% (46/67) patients were HRD positive and the rest 31.3% (21/67) were HRD negative. The PFS among HRD-positive patients was significantly longer than those HRD-negative patients (medium PFS 9.4 m vs 4.1 m, hazard ratio [HR]: 0.52, 95% CI: [0.38–0.71], p <0.001). Univariate cox-regression found that HRD status, Eastern Cooperative Oncology Group (ECOG) status, BRCA status, previous treatment lines, secondary cytoreductive surgery and R0 resection were significantly associated with PFS after PARPi treatment. After multiple regression correction, HRD status and ECOG were the independent factors to predict PFS (HR: 0.67, 95% CI: [0.49–0.92], p = 0.01; HR: 2.20, 95% CI: [1.14–4.23], p = 0.02, respectively). In platinum sensitivity evaluable subgroup (N = 49), HRD status and platinum sensitivity status remain significant to predict PFS after multiple regression correction (HR: 0.71, 95% CI: [0.51–0.98], p = 0.04; HR: 0.49, 95% CI: [0.24–1.0], p = 0.05, respectively). This is the first real-world study of HRD status in ovarian cancer patients in China, and we demonstrate that HRD is an independent predictive biomarker for PARP inhibitors treatment in Chinese ovarian cancer patients.