The role of the immune system in brain metastasis

Metastatic brain tumors are the most common brain tumors in adults. With numerous successful advancements in systemic treatment of most common cancer types, brain metastasis is becoming increasingly important in the overall prognosis of cancer patients. Brain metastasis of peripheral tumor is the result of complex interplay of primary tumor, immune system and central nervous system microenvironment. Once formed, brain metastases hide behind the blood brain barrier and become inaccessible to chemotherapies that are otherwise successful in targeting systemic cancer. The approval of immune checkpoint inhibitors for several common cancers such as advanced melanoma and lung cancers brings with it the opportunity and obligation to further understand the mechanisms of immunosuppression by tumors that spread to the brain as well as the interaction between the brain environment and tumor microenvironment. In this review paper we define the central role of the immune system in the development of brain metastases. We performed a comprehensive review of the literature to outline the molecular mechanisms of immunosuppression used by tumors and how the immune system interacts with the central nervous system to facilitate brain metastasis. In particular we discuss the tumor-type-specific mechanisms of metastasis of cancers that preferentially metastasize to the brain as well as the therapies that effectively modulate the immune response, such as immune checkpoint inhibitors and vaccines

Perspective: Melanoma diagnosis and monitoring: Sunrise for melanoma therapy but early detection remains in the shade

Last revised 25 Jul 2016.Melanoma is one of the most dangerous forms of cancer. The five-year survival rate is 98% if it is detected early. However, this rate plummets to 63% for regional disease and 17% when tumors have metastasized, that is, spread to distant sites. Furthermore, the incidence of melanoma has been rising by about 3% per year, whereas the incidence of cancers that are more common is decreasing. A handful of targeted therapies have recently become available that have finally shown real promise for treatment, but for reasons that remain unclear only a fraction of patients respond long term. These drugs often increase survival by only a few months in metastatic patient groups before relapse occurs. More effective treatment may be possible if a diagnosis can be made when the tumor burden is still low. Here, an overview of the current state-of-the-art is provided along with an argument for newer technologies towards early point-of-care diagnosis of melanoma

Can IDO activity predict primary resistance to anti-PD-1 treatment in NSCLC?

BACKGROUND: Immune checkpoint inhibitors have revolutionized the treatment paradigm of highly lethal malignancies like advanced non-small cell lung cancer (NSCLC), demonstrating long-term tumour control and extended patient survival. Unfortunately, only 25-30% of patients experience a durable benefit, while the vast majority demonstrate primary or acquired resistance. Recently, indoleamine 2,3-dioxygenase (IDO) activity has been proposed as a possible mechanism of resistance to anti-PD-1 treatment leading to an immunosuppressive microenvironment. METHODS: Pre-treatment serum concentrations of tryptophan (trp) and kynurenine (kyn) were measured by high-performance liquid chromatography tandem mass spectrometry in NSCLC patients treated with second-line nivolumab. The IDO activity was expressed with kyn/trp ratio. The associations between kyn/trp ratio and early progression, performance status (PS), age, sex, brain metastases, pleural effusion, progression free survival (PFS) and overall survival (OS) were analyzed using Spearman test and Mann-Whitney test. RESULTS: Twenty-six NSCLC patients were included in our study; 14 of them (54%) presented early progression (< 3 months) to nivolumab treatment. The median value of kyn/trp ratio was 0.06 µg/ml and the median value of quinolinic acid was 68.45 ng/ml. A significant correlation between early progression and higher kyn/trp ratio and quinolinic acid concentration was observed (p = 0.017 and p = 0.005, respectively). Patients presenting lower values of kyn/trp ratio and quinolinic acid levels showed longer PFS (median PFS not reached versus 3 months; HR: 0.3; p = 0.018) and OS (median OS not reached vs 3 months; HR: 0.18; p = 0.0005). CONCLUSION: IDO activity, expressed as kyn/trp ratio, is associated with response to immunotherapy; in particular, higher kyn/trp ratio could predict resistance to anti-PD-1 treatment. These preliminary results suggest the possibility of using anti-PD-1 plus IDO inhibitor in those patients with high level of kyn/trp ratio

Machine Learning Approaches to Predict Recurrence of Aggressive Tumors

Cancer recurrence is the major cause of cancer mortality. Despite tremendous research efforts, there is a dearth of biomarkers that reliably predict risk of cancer recurrence. Currently available biomarkers and tools in the clinic have limited usefulness to accurately identify patients with a higher risk of recurrence. Consequently, cancer patients suffer either from under- or over- treatment. Recent advances in machine learning and image analysis have facilitated development of techniques that translate digital images of tumors into rich source of new data. Leveraging these computational advances, my work addresses the unmet need to find risk-predictive biomarkers for Triple Negative Breast Cancer (TNBC), Ductal Carcinoma in-situ (DCIS), and Pancreatic Neuroendocrine Tumors (PanNETs). I have developed unique, clinically facile, models that determine the risk of recurrence, either local, invasive, or metastatic in these tumors. All models employ hematoxylin and eosin (H&E) stained digitized images of patient tumor samples as the primary source of data. The TNBC (n=322) models identified unique signatures from a panel of 133 protein biomarkers, relevant to breast cancer, to predict site of metastasis (brain, lung, liver, or bone) for TNBC patients. Even our least significant model (bone metastasis) offered superior prognostic value than clinopathological variables (Hazard Ratio [HR] of 5.123 vs. 1.397 p\u3c0.05). A second model predicted 10-year recurrence risk, in women with DCIS treated with breast conserving surgery, by identifying prognostically relevant features of tumor architecture from digitized H&E slides (n=344), using a novel two-step classification approach. In the validation cohort, our DCIS model provided a significantly higher HR (6.39) versus any clinopathological marker (p\u3c0.05). The third model is a deep-learning based, multi-label (annotation followed by metastasis association), whole slide image analysis pipeline (n=90) that identified a PanNET high risk group with over an 8x higher risk of metastasis (versus the low risk group p\u3c0.05), regardless of cofounding clinical variables. These machine-learning based models may guide treatment decisions and demonstrate proof-of-principle that computational pathology has tremendous clinical utility

Long non-coding RNAs in cutaneous melanoma : clinical perspectives

Metastatic melanoma of the skin has a high mortality despite the recent introduction of targeted therapy and immunotherapy. Long non-coding RNAs (lncRNAs) are defined as transcripts of more than 200 nucleotides in length that lack protein-coding potential. There is growing evidence that lncRNAs play an important role in gene regulation, including oncogenesis. We present 13 lncRNA genes involved in the pathogenesis of cutaneous melanoma through a variety of pathways and molecular interactions. Some of these lncRNAs are possible biomarkers or therapeutic targets for malignant melanoma

MicroRNA-203 predicts human survival after resection of colorectal liver metastasis.

BackgroundResection of colorectal liver metastasis (CRLM) can be curative. Predicting which patients may benefit from resection, however, remains challenging. Some microRNAs (miRNAs) become deregulated in cancers and contribute to cancer progression. We hypothesized that miRNA expression can serve as a prognostic marker of survival after CRLM resection.ResultsMiR-203 was significantly overexpressed in tumors of short-term survivors compared to long-term survivors. R1/R2 margin status and high clinical risk score (CRS) were also significantly associated with short-term survival (both p = 0.001). After adjusting for these variables, higher miR-203 expression remained an independent predictor of shorter survival (p = 0.010). In the serum cohort, high CRS and KRAS mutation were significantly associated with short-term survival (p = 0.005 and p = 0.026, respectively). After adjusting for CRS and KRAS status, short-term survivors were found to have significantly higher miR-203 levels (p = 0.016 and p = 0.033, respectively).Materials and methodsWe employed next-generation sequencing of small-RNAs to profile miRNAs in solid tumors obtained from 38 patients who underwent hepatectomy for CRLM. To validate, quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was performed on 91 tumor samples and 46 preoperative serum samples.ConclusionsAfter CRLM resection, short-term survivors exhibited significantly higher miR-203 levels relative to long-term survivors. MiR-203 may serve as a prognostic biomarker and its prognostic capacity warrants further investigation

A lab-on-a-disc platform enables serial monitoring of individual CTCs associated with tumor progression during EGFR-targeted therapy for patients with NSCLC

Rationale: Unlike traditional biopsy, liquid biopsy, which is a largely non-invasive diagnostic and monitoring tool, can be performed more frequently to better track tumors and mutations over time and to validate the efficiency of a cancer treatment. Circulating tumor cells (CTCs) are considered promising liquid biopsy biomarkers; however, their use in clinical settings is limited by high costs and a low throughput of standard platforms for CTC enumeration and analysis. In this study, we used a label-free, high-throughput method for CTC isolation directly from whole blood of patients using a standalone, clinical setting-friendly platform. Methods: A CTC-based liquid biopsy approach was used to examine the efficacy of therapy and emergent drug resistance via longitudinal monitoring of CTC counts, DNA mutations, and single-cell-level gene expression in a prospective cohort of 40 patients with epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer. Results: The change ratio of the CTC counts was associated with tumor response, detected by CT scan, while the baseline CTC counts did not show association with progression-free survival or overall survival. We achieved a 100% concordance rate for the detection of EGFR mutation, including emergence of T790M, between tumor tissue and CTCs. More importantly, our data revealed the importance of the analysis of the epithelial/mesenchymal signature of individual pretreatment CTCs to predict drug responsiveness in patients. Conclusion: The fluid-assisted separation technology disc platform enables serial monitoring of CTC counts, DNA mutations, as well as unbiased molecular characterization of individual CTCs associated with tumor progression during targeted therapy

The potential for liquid biopsies in the precision medical treatment of breast cancer.

Currently the clinical management of breast cancer relies on relatively few prognostic/predictive clinical markers (estrogen receptor, progesterone receptor, HER2), based on primary tumor biology. Circulating biomarkers, such as circulating tumor DNA (ctDNA) or circulating tumor cells (CTCs) may enhance our treatment options by focusing on the very cells that are the direct precursors of distant metastatic disease, and probably inherently different than the primary tumor's biology. To shift the current clinical paradigm, assessing tumor biology in real time by molecularly profiling CTCs or ctDNA may serve to discover therapeutic targets, detect minimal residual disease and predict response to treatment. This review serves to elucidate the detection, characterization, and clinical application of CTCs and ctDNA with the goal of precision treatment of breast cancer