Stem cell biomarkers for the diagnosis, prognosis and therapeutic stratification of human cancers
Adult tissue stem cells (SC) are a subpopulation of cells necessary for tissue integrity and regeneration in the case of injury. Their numbers within normal tissues are tightly controlled, but it is now widely accepted that these controls can malfunction in cancer, leading to an inappropriate expansion of the SC compartment and, ultimately, in the emergence of cancer stem cells (CSC) with tumorigenic and metastatic potential. Within the Novel Diagnostics Program, we have several ongoing projects focused on the characterization and clinical validation of CSC biomarkers in different solid cancers, with the ultimate aim of developing real clinical applications.
SC-based multigene assay for prognostic prediction in breast cancer
Breast cancers are remarkably heterogeneous in the molecular characteristics and clinical behavior, making it difficult to predict prognosis and therapy response in individual patients. Considering the increasingly recognized role of CSCs in driving tumor progression, therapy resistance and metastasis, we hypothesized that CSC-specific markers could be informative in the clinical management of breast cancer patients. Through the transcriptional profiling of purified normal human mammary SCs, we have identified a SC signature that is capable of stratifying breast cancers based on their degree of ‘stemness” . Our work has shown that aggressive, poor prognosis breast cancers have a “high stemness” profile, while less-aggressive, good prognosis breast have a “low stemness” profile. Thus, our SC signature could be useful in the prediction of prognosis in breast cancer patients.
In the Novel Diagnostics Program, we are working to translate these findings to the clinical setting by developing a prognostic toolkit based on our signature and validating our findings in various breast cancer cohorts. To date, we have developed a quantitative PCR-based test for the expression analysis of our SC signature in breast cancer biopsy samples (FFPE), and used this test to perform a retrospective-prospective analysis of a large breast cancer cohort. This analysis showed that our SC signature is able to predict risk of distant metastasis and provide prognostic information additional to standard clinicopathological parameters. We are now performing further validation studies aimed at increasing the level of evidence of the clinical validity of our SC signature and improving the clinical management of breast cancer.
Finally, we are exploiting pre-clinical breast cancer models (patient-derived xenografts) to perform a functional characterization of the SC biomarkers with a view to developing novel molecularly targeted therapies for breast cancer.
Identification and clinical validation of CSC biomarkers for prognostic prediction in prostate cancer
Tumor heterogeneity is a major hurdle in the individualized treatment of men with a diagnosis of prostate cancer, clouding decisions about the best therapeutic strategy to take and often resulting in the overtreatment of patients. Thus, there is an urgent need to develop more accurate prognostic biomarkers for prostate cancer to help prevent unnecessary and often harmful treatment of patients. Prostate cancer stem cells (PCSCs) have recently attracted attention in biomarker discovery attempts for aggressive prostate cancer, based on their posited role in driving primary tumor aggressiveness, therapy resistance to androgen-deprivation therapies and metastasis. By isolating and molecularly characterizing PCSCs, we have recently identified and validated a PCSC biomarker with potential prognostic and therapeutic significance in prostate cancer. Efforts in the Novel Diagnostics Programare now focused on determining the precise prognostic value of our candidate PCSC marker by retrospective analysis of prostate cancer patient cohorts. We are also investigating the therapeutic significance of targeting this biomarker, through in vitroand in vivostudies based on the use of primary prostate cancer cells. This novel PCSCmarker might therefore represent a valuable clinical tool in the individualized management of prostate cancer patients.
Validation of prognostic and therapeutic biomarkers in bladder cancer
Bladder cancer, despite being a major cause of cancer-related death, is one of the most understudied cancers. Consequently, little progress has been made in bladder cancer prognosis and treatment over the last decades, and the burden of this disease in terms of morbidity, mortality and related healthcare costs remains high. In the Novel Diagnostics Program, we are tackling this issue by characterizing “driver” alterations in the urothelial SC compartment that could lead to the identification of novel biomarkers and molecular targets for bladder cancer. Our group has already identified a candidate driver alteration in bladder cancer that we are currently validating using mouse models and biopsy specimens from bladder cancer patients.
Development of diagnostic and prognostic markers for early stage lung cancer
Lung cancer is the primary cause of cancer-related death worldwide. The National Lung Cancer Screening Trial has confirmed that lung cancer mortality can be reduced if tumors are diagnosed early, i.e., at stage I. However, a substantial fraction of stage I lung cancer patients still develop metastatic disease within 5 years from surgery. Thus, efforts need to be devoted to the development of effective strategies for early lung cancer detection, as well as the identification of prognostic biomarkers capable of predicting risk of relapse in early stage disease. Within the Novel Diagnostics Program, we have projects focused on both of these areas.
Development of a blood test for the early diagnosis of lung cancer
The absence of national screening programs for lung cancer and the lack of symptoms in early stage disease, render the detection of early lung cancer difficult. The development of clinical tools for the early diagnosis of lung cancer is, therefore, a pressing clinical need, particularly for at-risk subjects (e.g., smokers or ex-smokers, aged 50 years or more). To address this unmet need, we have developed a blood test, based on a circulating microRNA signature capable of detecting early stage lung cancer in asymptomatic patients [2-4]. In collaboration with the Division of Thoracic Surgery and the Division of Radiology, we are currently assessing the clinical validity of this test through the large-scale prospective multicenter COSMOS (Continuous Observation of Smoking Subjects) 2 trial coordinated by IEO. If validated, our blood test could represent a useful screening tool, to be used in combination with low-dose computer assisted tomography screening for early lung cancer detection, with the potential to greatly improve patient compliance to national lung cancer screening programs.
Development of prognostic signatures for early stage lung cancer
To date, a sizable fraction of stage I NSCLC patients (up to ~40%) develop disease recurrence within 5 years of surgery. Consequently, as our ability to detect NSCLC in its early stage improves, the issue of the clinical management of stage I patients is becoming increasingly relevant. Stage I NSCLC is treated preferentially by surgery, as the benefit of adjuvant chemotherapy in these patients remains controversial. However, prognostic biomarkers could change this scenario by allowing the stratification of stage I patients according to risk of disease recurrence and the selection of those patients who might benefit from multimodality treatment.
We previously described a 10-gene signature able to predict prognosis of patients with stage I lung adenocarcinoma, the major subtype of NSCLC [5,6], and developed a PCR-based method for assessing our 10-gene signature in FFPE tissue samples. Using this optimized PCR-based assay, we validated the prognostic accuracy of the 10-gene signature in an independent cohort of lung adenocarcinoma patients . We also demonstrated that this signature is capable of identifying a molecular subtype of stage I lung adenocarcinoma with characteristics remarkably similar to those of advanced lung cancer . Therefore, our signature might aid the identification of stage I patients who would benefit from multimodality treatment. Through the Novel Diagnostics Program, we are focusing efforts on the clinical validation of the 10-gene risk model using approaches such as retrospective-prospective validation studies on large cohorts of early lung cancer patients and prospective observational studies.
- Pece S, Tosoni D, Confalonieri S, Mazzarol G, Vecchi M, Ronzoni S, Bernard L, Viale G, Pelicci PG, Di Fiore PP. Biological and molecular heterogeneity of breast cancers correlates with their cancer stem cell content. 2010 Cell 140:62-73.
- Bianchi F, Nicassio F, Marzi M, Belloni E, Dall'olio V, Bernard L, Pelosi G, Maisonneuve P, Veronesi G, Di Fiore PP. A serum circulating miRNA diagnostic test to identify asymptomatic high-risk individuals with early stage lung cancer. 2011 EMBO Mol Med. 3:495-503.
- Montani F, Marzi MJ, Dezi F, Dama E, Carletti RM, Bonizzi G, Bertolotti R, Bellomi M, Rampinelli C, Maisonneuve P, Spaggiari L, Veronesi G, Nicassio F, Di Fiore PP, Bianchi F. miR-Test: a blood test for lung cancer early detection. 2015 JNCI 107(6):djv063.
- Marzi MJ, Montani F, Carletti RM, Dezi F, Dama E, Bonizzi G, Sandri MT, Rampinelli C, Bellomi M, Maisonneuve P, Spaggiari L, Veronesi G, Bianchi F, Di Fiore PP, Nicassio F. Optimization and Standardization of Circulating MicroRNA Detection for Clinical Application: The miR-Test Case. 2016 Clin Chem. 62:743-54.
- Bianchi F, Nuciforo P, Vecchi M, Bernard L, Tizzoni L, Marchetti A, Buttitta F, Felicioni L, Nicassio F, Di Fiore PP. Survival prediction of stage I lung adenocarcinomas by expression of 10 genes. 2007 J Clin Invest. 117:3436–44.
- Dama, E, Melocchi, V, Dezi, F, Pirroni, S, Carletti, RM, Brambilla, D, Bertalot, G, Casiraghi, M, Maisonneuve, P, Barberis, M, Viale, G, Vecchi, M, Spaggiari, L, Bianchi, F, Di Fiore, PP. An Aggressive Subtype of Stage I Lung Adenocarcinoma with Molecular and Prognostic Characteristics Typical of Advanced Lung Cancers. 2017 Clin Cancer Res. 23:62-72.