Review of precision cancer medicine: Evolution of the treatment paradigm.

In recent years, biotechnological breakthroughs have led to identification of complex and unique biologic features associated with carcinogenesis. Tumor and cell-free DNA profiling, immune markers, and proteomic and RNA analyses are used to identify these characteristics for optimization of anticancer therapy in individual patients. Consequently, clinical trials have evolved, shifting from tumor type-centered to gene-directed, histology-agnostic, with innovative adaptive design tailored to biomarker profiling with the goal to improve treatment outcomes. A plethora of precision medicine trials have been conducted. The majority of these trials demonstrated that matched therapy is associated with superior outcomes compared to non-matched therapy across tumor types and in specific cancers. To improve the implementation of precision medicine, this approach should be used early in the course of the disease, and patients should have complete tumor profiling and access to effective matched therapy. To overcome the complexity of tumor biology, clinical trials with combinations of gene-targeted therapy with immune-targeted approaches (e.g., checkpoint blockade, personalized vaccines and/or chimeric antigen receptor T-cells), hormonal therapy, chemotherapy and/or novel agents should be considered. These studies should target dynamic changes in tumor biologic abnormalities, eliminating minimal residual disease, and eradicating significant subclones that confer resistance to treatment. Mining and expansion of real-world data, facilitated by the use of advanced computer data processing capabilities, may contribute to validation of information to predict new applications for medicines. In this review, we summarize the clinical trials and discuss challenges and opportunities to accelerate the implementation of precision oncology

Neoadjuvant treatment in ovarian cancer: New perspectives, new challenges

Ovarian cancer remains the leading cause of death from gynecological cancer. Survival is significantly related to the stage of the disease at diagnosis. Of quite importance is primary cytoreductive surgery, having as a goal to remove all visible tumor tissue, and is the standard primary treatment in combination with platinum-based chemotherapy for patients with advanced ovarian carcinoma.Neo-adjuvant chemotherapy (NACT) has been implemented mostly in treating advanced disease, with studies performed having numerous limitations. Data extrapolated from these studies have not shown inferiority survival of NACT, compared to primary debulking surgery. The role of NACT is of particular interest because of the intrinsic mechanisms that are involved in the process, which can be proven as therapeutic approaches with enormous potential. NACT increases immune infiltration and programmed death ligand-1 (PDL-1) expression, induces local immune activation, and can potentiate the immunogenicity of immune-exclude high grade serous ovarian tumors, while the combination of NACT with bevacizumab, PARP inhibitors or immunotherapy remains to be evaluated. This article summarizes all available data on studies implementing NACT in the treatment of ovarian cancer, focusing on clinical outcomes and study limitations. High mortality rates observed among ovarian cancer patients necessitates the identification of more effective treatments, along with biomarkers that will aid treatment individualization

Carboplatin-Induced Gene Expression Changes In Vitro are Prognostic of Survival in Epithelial Ovarian Cancer

Background: We performed a time-course microarray experiment to define the transcriptional response to carboplatin in vitro, and to correlate this with clinical outcome in epithelial ovarian cancer (EOC). RNA was isolated from carboplatin and control-treated 36M2 ovarian cancer cells at several time points, followed by oligonucleotide microarray hybridization. Carboplatin induced changes in gene expression were assessed at the single gene as well as at the pathway level. Clinical validation was performed in publicly available microarray datasets using disease free and overall survival endpoints. Results: Time-course and pathway analyses identified 317 genes and 40 pathways (designated time-course and pathway signatures) deregulated following carboplatin exposure. Both types of signatures were validated in two separate platinum-treated ovarian and NSCLC cell lines using published microarray data. Expression of time-course and pathway signature genes distinguished between patients with unfavorable and favorable survival in two independent ovarian cancer datasets. Among the pathways most highly induced by carboplatin in vitro, the NRF2, NF-kB, and cytokine and inflammatory response pathways were also found to be upregulated prior to chemotherapy exposure in poor prognosis tumors. Conclusion: Dynamic assessment of gene expression following carboplatin exposure in vitro can identify both genes and pathways that are correlated with clinical outcome. The functional relevance of this observation for better understanding the mechanisms of drug resistance in EOC will require further evaluation

Analysis of Multiple Sarcoma Expression Datasets: Implications for Classification, Oncogenic Pathway Activation and Chemotherapy Resistance

Background: Diagnosis of soft tissue sarcomas (STS) is challenging. Many remain unclassified (not-otherwise-specified, NOS) or grouped in controversial categories such as malignant fibrous histiocytoma (MFH), with unclear therapeutic value. We analyzed several independent microarray datasets, to identify a predictor, use it to classify unclassifiable sarcomas, and assess oncogenic pathway activation and chemotherapy response. Methodology/Principal Findings: We analyzed 5 independent datasets (325 tumor arrays). We developed and validated a predictor, which was used to reclassify MFH and NOS sarcomas. The molecular “match” between MFH and their predicted subtypes was assessed using genome-wide hierarchical clustering and Subclass-Mapping. Findings were validated in 15 paraffin samples profiled on the DASL platform. Bayesian models of oncogenic pathway activation and chemotherapy response were applied to individual STS samples. A 170-gene predictor was developed and independently validated (80-85% accuracy in all datasets). Most MFH and NOS tumors were reclassified as leiomyosarcomas, liposarcomas and fibrosarcomas. “Molecular match” between MFH and their predicted STS subtypes was confirmed both within and across datasets. This classification revealed previously unrecognized tissue differentiation lines (adipocyte, fibroblastic, smooth-muscle) and was reproduced in paraffin specimens. Different sarcoma subtypes demonstrated distinct oncogenic pathway activation patterns, and reclassified MFH tumors shared oncogenic pathway activation patterns with their predicted subtypes. These patterns were associated with predicted resistance to chemotherapeutic agents commonly used in sarcomas. Conclusions/Significance: STS profiling can aid in diagnosis through a predictor tracking distinct tissue differentiation in unclassified tumors, and in therapeutic management via oncogenic pathway activation and chemotherapy response assessment

Vinorelbine-based salvage therapy in HER2-positive metastatic breast cancer patients progressing during trastuzumab-containing regimens: a retrospective study

<p>Abstract</p> <p>Background</p> <p>The vinka-alkaloyd vinorelbine is a potentially valuable treatment in patients with HER2-positive, trastuzumab-resistant advanced breast cancer. We sought to document the clinical activity of vinorelbine-based salvage treatments in this clinical setting.</p> <p>Methods</p> <p>We analyzed a cohort of 424 consecutive women receiving trastuzumab-based therapy for HER2-positive advanced breast cancer. Of these, 299 were identified as progressing during the initial trastuzumab-based treatment, and 77 received vinorelbine-based therapy as first salvage treatment. Central review of pathological specimens revealed that 70 patients had HER2-amplification detected by FISH. For these patients we determined overall response rate (ORR = complete-CR + partial-PR) and clinical benefit (CB = CR+PR+ Stable disease lasting at least 6 months), time to progression (TTP) and overall survival (OS) from the initiation of vinorelbine-based salvage therapy.</p> <p>Results</p> <p>In 60 patients who were evaluable for tumor response, ORR and CB rates were 28% (95% C.I. 18%-41%) and 50% (95% C.I. 38%-62%), respectively. Median follow-up from the initiation of salvage therapy was 15 months (range 1–63 months). Median TTP and OS were 7.1 months (95% C.I. 6.6–7.7 months) and 21 months (95% C.I. 14.3–27.7 months), respectively. No differences in clinical outcomes were observed according to whether vinorelbine was administered as a single agent or in combination with other cytostatics, or whether trastuzumab was stopped or continued beyond disease progression.</p> <p>Conclusion</p> <p>our findings suggests that vinorelbine-based combinations are active and should be further evaluated in studies conducted in trastuzumab-resistant patients, including those evaluating newer HER2-targeting agents.</p

Angiogenesis in cancer of unknown primary: clinicopathological study of CD34, VEGF and TSP-1

BACKGROUND: Cancer of unknown primary remains a mallignancy of elusive biology and grim prognosis that lacks effective therapeutic options. We investigated angiogenesis in cancer of unknown primary to expand our knowledge on the biology of these tumors and identify potential therapeutic targets. METHODS: Paraffin embedded archival material from 81 patients diagnosed with CUP was used. Tumor histology was adenocarcinoma (77%), undifferentiated carcinoma (18%) and squamous cell carcinoma (5%). The tissue expression of CD34, VEGF and TSP-1 was assessed immunohistochemically by use of specific monoclonal antibodies and was analyzed against clinicopathological data. RESULTS: VEGF expression was detected in all cases and was strong in 83%. Stromal expression of TSP-1 was seen in 80% of cases and was strong in 20%. The expression of both proteins was not associated with any clinical or pathological parameters. Tumor MVD was higher in tumors classified as unfavorable compared to more favorable and was positively associated with VEGF and negatively with TSP-1. CONCLUSION: Angiogenesis is very active and expression of VEGF is almost universal in cancers of unknown primary. These findings support the clinical investigation of VEGF targeted therapy in this clinical setting

Carboplatin-induced gene expression changes in vitro are prognostic of survival in epithelial ovarian cancer

<p>Abstract</p> <p>Background</p> <p>We performed a time-course microarray experiment to define the transcriptional response to carboplatin <it>in vitro</it>, and to correlate this with clinical outcome in epithelial ovarian cancer (EOC). RNA was isolated from carboplatin and control-treated 36M2 ovarian cancer cells at several time points, followed by oligonucleotide microarray hybridization. Carboplatin induced changes in gene expression were assessed at the single gene as well as at the pathway level. Clinical validation was performed in publicly available microarray datasets using disease free and overall survival endpoints.</p> <p>Results</p> <p>Time-course and pathway analyses identified 317 genes and 40 pathways (designated time-course and pathway signatures) deregulated following carboplatin exposure. Both types of signatures were validated in two separate platinum-treated ovarian and NSCLC cell lines using published microarray data. Expression of time-course and pathway signature genes distinguished between patients with unfavorable and favorable survival in two independent ovarian cancer datasets. Among the pathways most highly induced by carboplatin <it>in vitro</it>, the NRF2, NF-kB, and cytokine and inflammatory response pathways were also found to be upregulated prior to chemotherapy exposure in poor prognosis tumors.</p> <p>Conclusion</p> <p>Dynamic assessment of gene expression following carboplatin exposure <it>in vitro </it>can identify both genes and pathways that are correlated with clinical outcome. The functional relevance of this observation for better understanding the mechanisms of drug resistance in EOC will require further evaluation.</p

Gene expression profiling in laryngeal cancer

IntroductionLaryngeal cancer is the eleventh most common type of cancer in menworldwide. Despite the improvement in diagnostic and therapeutic techniques,some patients still recur after treatment. Known prognostic factors cannot adequatelypredict which patients will recur. Additional factors are therefore requiredto further refine the assessment of risk of recurrence. Previous studieson the expression profiling of head and neck cancer have identified predictorsof recurrence and lymphatic metastasis. Further studies, focused on head andneck cancer of a specific site and accompanied by external validation of theresults, are needed in order to identify a more robust prognostic profile.PurposeThe aim of this study was to identify gene expression models, prognosticof disease-free survival (DFS) in primary laryngeal cancer.Patients and MethodsIn the first part of the analysis, Affymetrix U133A Genechips were used,to profile fresh-frozen tumor tissues from two cohorts of 66 and 54 patientswith laryngeal cancer, treated locally with surgery (training set and 1st validationsets). Formalin-fixed paraffin-embedded tissue samples from 194 patientswere used to further validate our results (2nd validation set). In the secondpart of the analysis, profiles prognostic of recurrence were identified in 61 patientswith early stage laryngeal cancer. Profiling was performed using wholegenome 24K DASL (c-DNA-mediated, Annealing, Selection and Ligation)arrays, (Illumina, CA).94ResultsIn the training set, we focused on genes univariately associated with DFS(p<0.01). Cox regression proportional hazards modeling was applied to identifyseveral gene models prognostic of recurrence, including a 30-gene model thatdemonstrated optimal performance (log-rank, p<0.001). These multigenepredictors were then directly applied to the 1st validation set, with similarresults being observed. Furthermore, unsupervised hierarchical clusteringbased on the expression of specific genes of the 30-gene model yielded twogroups, in the 2nd validation set, which differed significantly in DFS (HR=2.26,95% CI 1.08-4.76, p=0.031).ConclusionsWe have established and validated gene models that can successfullystratify patients with laryngeal cancer, based on their risk for recurrence. Thesefindings, if further validated, could aid in the stratification of patients fortesting novel adjuvant treatment strategiesΕισαγωγήO καρκίνος του λάρυγγα είναι ο ενδέκατος κατά σειρά συχνότητας τωνκαρκίνων στον άνδρα παγκοσμίως. Παρά τη συνεχή βελτίωση των διαγνω-στικών και θεραπευτικών μεθόδων, ένα σημαντικό ποσοστό των ασθενών μεχειρουργήσιμο καρκίνο του λάρυγγα τελικά υποτροπιάζει. Επομένως, προ-κύπτει η ανάγκη ανακάλυψης και επιβεβαίωσης νέων προγνωστικών παρα-γόντων ώστε να βελτιωθεί η εκτίμηση της επικινδυνότητας υποτροπής. Προη-γούμενες μελέτες γονιδιακής έκφρασης των καρκίνων της κεφαλής και τουτραχήλου έχουν προσδιορίσει προγνωστικές γονιδιακές υπογραφές. Για τηνανάδειξη όμως ενός αξιόπιστου προγνωστικού μοντέλου είναι απαραίτητηη διεξαγωγή μελετών εστιασμένων σε μία ανατομική περιοχή, οι οποίες θασυνοδεύονται και από ανεξάρτητη επιβεβαίωση των αποτελεσμάτων.Σκοπός της μελέτηςΣκοπός αυτής της μελέτης είναι ο προσδιορισμός και επιβεβαίωση γο-νιδιακών υπογραφών, προγνωστικών της επιβίωσης ελεύθερης υποτροπήςσε ασθενείς με πρωτοπαθή καρκίνο του λάρυγγα.Ασθενείς και ΜέθοδοιΣτο πρώτο μέρος της ανάλυσης χρησιμοποιήθηκαν μικροσυστοιχίεςDNA Affymetrix U133A, ώστε να μελετήσουμε τη γονιδιακή έκφραση πρό-σφατα κατεψυγμένων ιστών 66 και 54 ασθενών με καρκίνο του λάρυγγα (ομά-δες άσκησης και 1η ομάδα τεκμηρίωσης). Υλικό, επεξεργασμένο με φορμόληκαι εγκλεισμένο σε παραφίνη, από τον πρωτοπαθή όγκο 194 ασθενών, χρη-σιμοποιήθηκε για την περαιτέρω επιβεβαίωση των αποτελεσμάτων (2η ομάδατεκμηρίωσης). Στο δεύτερο μέρος της διδακτορικής διατριβής, προσδιορίσαμε92προγνωστικές γονιδιακές υπογραφές σε 61 ασθενείς με καρκίνο του λάρυγγααρχικού σταδίου. Επιλέχθηκε η πλατφόρμα 24Κ Whole Genome DASL assay(c-DNA-mediated, Annealing, Selection and Ligation) arrays, (Illumina, CA).ΑποτελέσματαΕστιάσαμε στα γονίδια που σχετίζονταν μονοπαραγοντικά με την επι-βίωση ελεύθερη υποτροπής (p<0.01) στην ομάδα άσκησης. Εφαρμόσαμε τομοντέλο αναλογικού κινδύνου κατά Cox και προσδιορίσαμε πολλαπλά προ-γνωστικά γονιδιακά μοντέλα. Καταλήξαμε σε ένα μοντέλο 30 γονιδίων τοοποίο είχε την καλύτερη επίδοση στον διαχωρισμό ασθενών με βάση την επι-βίωση ελεύθερη υποτροπής (log-rank test, p<0.001). Ακολούθως, εφαρμόσαμετις προγνωστικές γονιδιακές υπογραφές στην 1η ομάδα τεκμηρίωσης και πα-ρατηρήσαμε αντίστοιχα αποτελέσματα. Στη συνέχεια, στη 2η ομάδα τεκμη-ρίωσης, χρησιμοποιώντας τον αλγόριθμο ιεραρχικής ομαδοποίησης στη γο-νιδιακή έκφραση των 30 γονιδίων προέκυψαν δύο ομάδες ασθενών με στα-τιστικά σημαντική διαφορά στην επιβίωση ελεύθερη υποτροπής (HR=2.26,95%CI 1.08-4.76, p=0.031).ΣυμπεράσματαΣτην παρούσα μελέτη προσδιορίστηκαν και επιβεβαιώθηκαν γονιδιακάμοντέλα, τα οποία μπορούν να κατηγοριοποιήσουν τους ασθενείς με καρκίνοτου λάρυγγα βάσει του κινδύνου υποτροπής

Transcriptomics and solid tumors: The next frontier in precision cancer medicine.

Transcriptomics, which encompasses assessments of alternative splicing and alternative polyadenylation, identification of fusion transcripts, explorations of noncoding RNAs, transcript annotation, and discovery of novel transcripts, is a valuable tool for understanding cancer mechanisms and identifying biomarkers. Recent advances in high-throughput technologies have enabled large-scale gene expression profiling. Importantly, RNA expression profiling of tumor tissue has been successfully used to determine clinically actionable molecular alterations. The WINTHER precision medicine clinical trial was the first prospective trial in diverse solid malignancies that assessed both genomics and transcriptomics to match treatments to specific molecular alterations. The use of transcriptome analysis in WINTHER and other trials increased the number of targetable -omic changes compared to genomic profiling alone. Other applications of transcriptomics involve the evaluation of tumor and circulating noncoding RNAs as predictive and prognostic biomarkers, the improvement of risk stratification by the use of prognostic and predictive multigene assays, the identification of fusion transcripts that drive tumors, and an improved understanding of the impact of DNA changes as some genomic alterations are silenced at the RNA level. Finally, RNA sequencing and gene expression analysis have been incorporated into clinical trials to identify markers predicting response to immunotherapy. Many issues regarding the complexity of the analysis, its reproducibility and variability, and the interpretation of the results still need to be addressed. The integration of transcriptomics with genomics, proteomics, epigenetics, and tumor immune profiling will improve biomarker discovery and our understanding of disease mechanisms and, thereby, accelerate the implementation of precision oncology