Molecular Markers to Predict Prognosis and Treatment Response in Uterine Cervical Cancer

Abstract

Uterine cervical cancer is one of the leading causes of cancer-related mortality in women worldwide. Each year, over half a million new cases are estimated, resulting in more than 300,000 deaths. While less-invasive, fertility-preserving surgical procedures can be offered to women in early stages, treatment for locally advanced disease may include radical hysterectomy, primary chemoradiotherapy (CRT) or a combination of these modalities. Concurrent platinum-based chemoradiotherapy regimens remain the first-line treatments for locally advanced cervical cancer. Despite achievements such as the introduction of angiogenesis inhibitors, and more recently immunotherapies, the overall survival of women with persistent, recurrent or metastatic disease has not been extended significantly in the last decades. Furthermore, a broad spectrum of molecular markers to predict therapy response and survival and to identify patients with high- and low-risk constellations is missing. Implementation of these markers, however, may help to further improve treatment and to develop new targeted therapies. This review aims to provide comprehensive insights into the complex mechanisms of cervical cancer pathogenesis within the context of molecular markers for predicting treatment response and prognosis.

Keywords: biomarker; cervical cancer; chemoradiotherapy; molecular marker; outcome; predictive; prognostic; response; survival.

Figure 1

Clinical risk factors in cervical cancer. After primary, curatively intended surgery, Sedlis’ and Peters’ criteria were established to estimate the risk of pelvic and extra-pelvic recurrence. These risk factors include tumor size, deep stromal invasion, involved parametria, lymphovascular space invasion (LVSI) and the presence of lymph node metastases. Created with BioRender.com (accessed on 5 September 2021).

Figure 2

E6 and E7 increase radiosensitivity of HPV-positive cervical cancer cells. An increased sensitivity to radiation by HPV-positive malignancies has been linked to several signaling pathways, including regulation of cell cycle progression, apoptosis and chromosomal instability. Shown is a simplified illustration of DNA damage repair signaling pathways impaired by altered TP53 and p16 activity. After the downregulation of retinoblastoma protein (Rb) by viral oncoprotein E7, increasing p16 levels hamper homologous recombination (HR) regulated via cyclin D1 and subsequently the RAD51/BRCA2 axis. Rb loss further diminishes the non-homologous end-joining (NHEJ) repair pathway. Cell cycle progression and G1-S transition are promoted by the release of the transcription factor E2F and the inhibition of cyclin-dependent kinase (CDK) inhibitors p21 and p27, while in contrast frequently triggered G2/M arrest reorders and arrests cancer cells at vulnerable stages of the cell cycle. Abbreviations: ATM: ataxia telangiectasia mutated; CHK2: checkpoint kinase 2; HPV: human papilloma virus. Adapted from “P53 Regulation and Signaling”, by BioRender.com (accessed on 2021). Retrieved from https://app.biorender.com/biorender-templates (accessed on October 2021).

Figure 3

Exemplary illustration of dysregulated signaling pathways and their interactions in cervical cancer. The schematic shows the nexus of dysregulated, activated or discontinued signaling pathways related to PLK3. Upon activation by DNA damage, hypoxic or oxidative stress PLK3 is activated and impacts on apoptosis, cell cycle progression, proliferation and survival. Details are given in the text. Abbreviations: Casp8: caspase 8, Casp3: caspase 3; Chk2: checkpoint kinase 2 FADD: Fas-associated protein with death domain; HIF1a: hypoxia-inducible factor 1-alpha; PARP: poly (ADP-ribose) polymerase; PLK3: polo-like kinase 3, PTEN: phosphatase and tensin homolog; VEGF: vascular endothelial growth factor. Adapted from “FAS Activation Pathway Initiates Cancer Cell Apoptosis” and “Novel Pharmacotherapies for Diabetic Macular Edema (DME)”, by BioRender.com (accessed on 2021). Retrieved from https://app.biorender.com/biorender-templates (accessed on October 2021).

Figure 4

Tumor microenvironment in cervical cancer (1). Immune cells, endothelial cells, fibroblasts, signaling proteins and extracellular matrix molecules within the tumor TME and in lymph nodes impact on tumor biology, therapy response and survival. The adaptive antitumor immune response is mainly mediated by activated CD8+ T cells, while regulatory T cells (Tregs) and myeloid-derived suppressor cells suppress the immune response (2). Further, the polarization status of tumor associated macrophages (TAMs) impact on treatment response and survival, while natural killer (NK) cell activity is modulated and hindered by HPV+ tumor cells (3). Moreover, cancer-associated fibroblasts (CAFs) promote apoptotic resistance, proliferation, angiogenesis, inflammation, invasion and metastatic spread of cancer cells in a paracrine manner (4). Details are given in the text. Abbreviations: CTLA4: cytotoxic T-lymphocyte-associated protein 4; COX2: cyclooxygenase 2; GM-CSF: granulocyte macrophage colony-stimulating factor; PD1: programmed death 1; SDF-1: stromal cell-derived factor 1; TCR: T-cell receptor; TGF-ß1 transforming growth factor beta 1. Adapted from “T Cell Deactivation vs. Activation”, “Tumor-Specific T Cell Induction and Function” and “Cancer Cell Mutations Affect Tumor Microenvironment”, by BioRender.com (accessed on 2021). Retrieved from https://app.biorender.com/biorender-templates (accessed on October 2021).