TIMP1 is an early biomarker for detection and prognosis of lung cancer

BACKGROUND

Lung cancer remains the major cause of cancer-related deaths worldwide. Early stages of lung cancer are characterized by long asymptomatic periods that are ineffectively identified with the current screening programs. This deficiency represents a lost opportunity to improve the overall survival of patients. Serum biomarkers are among the most effective strategies for cancer screening and follow up.

METHODS

Using bead-based multiplexing assays we screened plasma and tumours of the KrasG12D/+; Lkb1f/f (KL) mouse model of lung cancer for cytokines that could be used as biomarkers. We identified tissue inhibitor of metalloproteinase 1 (TIMP1) as an early biomarker and validated this finding in the plasma of lung cancer patients. We used immunohistochemistry (IHC), previously published single-cell RNA-seq and bulk RNA-seq data to assess the source and expression of TIMP1in the tumour. The prognostic value of TIMP1 was assessed using publicly available human proteomic and transcriptomic databases.

RESULTS

We found that TIMP1 is a tumour-secreted protein with high sensitivity and specificity for aggressive cancer, even at early stages in mice. We showed that TIMP1 levels in the tumour and serum correlate with tumour burden and worse survival in mice. We validated this finding using clinical samples from our institution and publicly available human proteomic and transcriptomic databases. These data support the finding that high tumour expression of TIMP1 correlates with an unfavorable prognosis in lung cancer patients.

CONCLUSION

TIMP1 is a suitable biomarker for lung cancer detection.

Abstract 2378: Methylmalonic acid is elevated in non-small cell lung cancer and promotes drug resistance

Lung cancer is the leading cause of cancer-related deaths in the United States. Identifying new factors that promote drug resistance is critical to restoring drug sensitivity and improving patient outcomes. Methylmalonic acid (MMA) is a dicarboxylic acid by-product of propionate metabolism. MMA levels rise in the serum with age and are associated with cancer-related mortality (the higher the MMA, the worse the mortality). We recently asked whether this metabolite had a functional impact and showed that treating non-small cell lung cancer (NSCLC) cells with MMA in vitro promotes drug resistance through triggering epithelial-to-mesenchymal transition (EMT). However, whether MMA is elevated in lung cancer is not known, and how MMA levels are regulated is poorly understood.

To determine if MMA is elevated in NSCLC, we performed targeted metabolomics on 20 resected lung adenocarcinomas and squamous cell carcinomas with matched normal lung tissue. We found that MMA was 2.5 fold elevated in tumors compared to controls (p<0.001, paired t-test). To our knowledge, this is the first report of MMA being elevated in any cancer. MMAB is one of the key MMA regulatory genes. When MMAB is inactivated or underexpressed, MMA cannot be metabolized and its intracellular levels increase. We hypothesized that loss of MMAB expression may explain elevated MMA levels in lung cancer. To test this, we analyzed publicly available mRNA expression data sets and found that MMAB is underexpressed in NSCLC (suggesting high levels of MMA). Moreover, MMAB expression correlates with survival. The lower the MMAB expression (suggesting higher MMA), the worse the survival (Hazard Ratio 0.36, p<0.001). We thus asked if suppressing MMAB expression had a functional impact on cell lines. Using shRNA constructs, we knocked down MMAB in the A549 and H1975 NSCLC cell lines. Targeted metabolomics confirmed that knockdown of MMAB increased MMA levels. Moreover, knockdown of MMAB decreased cellular proliferation and increased resistance to carboplatin, pemetrexed, and osimertinib. RNA-seq analysis showed that suppressing MMAB induced EMT and senescence expression signatures. Furthermore, we found that hypoxia and nutrient stress downregulate MMAB expression at the mRNA and protein level. Collectively, our data suggest that loss of MMAB expression through hypoxia or nutrient stress can increase MMA levels, triggering EMT and resistance to chemotherapy and targeted therapy in NSCLC. Our results indicate that dysregulation of MMA plays an important role in lung cancer.

Citation Format: Bobak Parang, Zhongchi Li, Vivien Low, Jennifer Endress, Murtaza Malbari, Ashish Saxena, Nasser Altorki, John Blenis. Methylmalonic acid is elevated in non-small cell lung cancer and promotes drug resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2378.

Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

In many areas of oncology, we lack sensitive tools to track low-burden disease. Although cell-free DNA (cfDNA) shows promise in detecting cancer mutations, we found that the combination of low tumor fraction (TF) and limited number of DNA fragments restricts low-disease-burden monitoring through the prevailing deep targeted sequencing paradigm. We reasoned that breadth may supplant depth of sequencing to overcome the barrier of cfDNA abundance. Whole-genome sequencing (WGS) of cfDNA allowed ultra-sensitive detection, capitalizing on the cumulative signal of thousands of somatic mutations observed in solid malignancies, with TF detection sensitivity as low as 10-5. The WGS approach enabled dynamic tumor burden tracking and postoperative residual disease detection, associated with adverse outcome. Thus, we present an orthogonal framework for cfDNA cancer monitoring via genome-wide mutational integration, enabling ultra-sensitive detection, overcoming the limitation of cfDNA abundance and empowering treatment optimization in low-disease-burden oncology care.

Abstract 3247: Genome-wide cell-free DNA mutation integration for sensitive cancer detection

Solid malignancies are often diagnosed at a late stage with dismal prognosis. Even after cancer is diagnosed, we lack sensitive tools to guide difficult therapeutic decisions such as adjuvant therapy. Sensitive cancer detection by blood biopsy can therefore transform care by enabling early detection and residual disease monitoring.

Cell free DNA mutation detection has shown significant promise in its ability to survey the somatic genome and enable detection of cancer mutations in the peripheral blood. However, the combination of low tumor fraction and limiting number of DNA fragments in a typical plasma sample, restrict the probability of detecting early stage cancer in cfDNA through current deep targeted sequencing methods.

Focusing on non-small cell lung cancer (NSCLC), we reasoned that we would need to supplant depth of sequencing with breadth of sequencing to overcome the fundamental limitation of low input of cfDNA. To do so, we apply whole genome sequencing (WGS) that allows us to base sensitive detection on the cumulative signal provided by 10,000-30,000 somatic mutations observed in a substantial proportion of NSCLC. We developed an analytic method that integrates genome-wide mutation signal to obtain a tumor fraction (TF) estimate, and thus allow sensitive detection of residual disease and quantitative dynamic monitoring of disease burden. Benchmarking on artificial plasma showed TF detection sensitivity as low as 1:100,000, two orders of magnitude more sensitive than currently available methods.

To test this method, we performed WGS on resected NSCLC and matched germline samples of 8 NSCLC patients, as well as on matched pre- and post-surgery cfDNA. Patient-specific somatic mutations were identified in the tumor/normal pairs and used for the estimation of TF in the matched plasma samples. We detect pre-surgery circulating tumor DNA (ctDNA) in all of the early-stage pre-operative samples and in ~40% post-operative patients, correlated with post-operative disease progression.

In early cancer detection, tumor DNA is not available, requiring de-novo mutation detection in cfDNA. To do so, we first trained a convolutional neuronal network to distinguish between cancer altered sequencing reads and reads affected by sequencing errors. This was followed by genome-wide pattern matching to a specific genomic signature that mark lung cancer mutations (Tobacco signature) indicating the presence of ctDNA in the patient plasma. Applying this method to the pre-operative early stage lung cancer samples and plasma samples from 5 patients with benign nodules (CT-detected) showed an accurate discrimination between malignant and benign nodules, suggesting a potential role in improving the positive predictive value of lung cancer screening in at-risk populations.

These results show that genome-wide mutation integration is a promising novel approach for ultra-sensitive early detection and residual disease monitoring.

Citation Format: Asaf Zviran, Steven T. Hill, Rafael Schulman, Minita Shah, Sunil Deochand, Gavin Ha, Sarah Reed, Denisse Rotem, Greg Gydush, Justin Rhoades, Kevin Huang, Will Liao, Dillon Maloney, Nathan Omans, Murtaza Malbari, Cathy F. Spinelli, Selena Kazancioglu, Nicolas Robine, Viktor Adalsteinsson, Brian Houck-Loomis, Nasser Altorki, Dan A. Landau. Genome-wide cell-free DNA mutation integration for sensitive cancer detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3247.