Grading of lung adenocarcinomas with simultaneous segmentation by artificial intelligence (GLASS-AI).

Preclinical genetically engineered mouse models (GEMMs) of lung adenocarcinoma are invaluable for investigating molecular drivers of tumor formation, progression, and therapeutic resistance. However, histological analysis of these GEMMs requires significant time and training to ensure accuracy and consistency. To achieve a more objective and standardized analysis, we used machine learning to create GLASS-AI, a histological image analysis tool that the broader cancer research community can utilize to grade, segment, and analyze tumors in preclinical models of lung adenocarcinoma. GLASS-AI demonstrates strong agreement with expert human raters while uncovering a significant degree of unreported intratumor heterogeneity. Integrating immunohistochemical staining with high-resolution grade analysis by GLASS-AI identified dysregulation of Mapk/Erk signaling in high-grade lung adenocarcinomas and locally advanced tumor regions. Our work demonstrates the benefit of employing GLASS-AI in preclinical lung adenocarcinoma models and the power of integrating machine learning and molecular biology techniques for studying the molecular pathways that underlie cancer progression.

CX3CR1 deficiency-induced TIL tumor restriction as a novel addition for CAR-T design in solid malignancies.

Advances in the understanding of the tumor microenvironment have led to development of immunotherapeutic strategies, such as chimeric antigen receptor T cells (CAR-Ts). However, despite success in blood malignancies, CAR-T therapies in solid tumors have been hampered by their restricted infiltration. Here, we used our understanding of early cytotoxic lymphocyte infiltration of human lymphocytes in solid tumors in vivo to investigate the receptors in normal, adjacent, and tumor tissues of primary non-small-cell lung cancer specimens. We found that CX3CL1-CX3CR1 reduction restricts cytotoxic cells from the solid-tumor bed, contributing to tumor escape. Based on this, we designed a CAR-T construct using the well-established natural killer group 2, member D (NKG2D) CAR-T expression together with overexpression of CX3CR1 to promote their infiltration. These CAR-Ts infiltrate tumors at higher rates than control-activated T cells or IL-15-overexpressing NKG2D CAR-Ts. This construct also had similar functionality in a liver-cancer model, demonstrating potential efficacy in other solid malignancies.

Spatial transcriptomics analysis identifies a unique tumor-promoting function of the meningeal stroma in melanoma leptomeningeal disease.

Leptomeningeal disease (LMD) remains a rapidly lethal complication for late-stage melanoma patients. The inaccessible nature of the disease site and lack of understanding of the biology of this unique metastatic site are major barriers to developing efficacious therapies for patients with melanoma LMD. Here, we characterize the tumor microenvironment of the leptomeningeal tissues and patient-matched extra-cranial metastatic sites using spatial transcriptomic analyses with in vitro and in vivo validation. We show the spatial landscape of melanoma LMD to be characterized by a lack of immune infiltration and instead exhibit a higher level of stromal involvement. We show that the tumor-stroma interactions at the leptomeninges activate pathways implicated in tumor-promoting signaling, mediated through upregulation of SERPINA3 at the tumor-stroma interface. Our functional experiments establish that the meningeal stroma is required for melanoma cells to survive in the CSF environment and that these interactions lead to a lack of MAPK inhibitor sensitivity in the tumor. We show that knocking down SERPINA3 or inhibiting the downstream IGR1R/PI3K/AKT axis results in re-sensitization of the tumor to MAPK-targeting therapy and tumor cell death in the leptomeningeal environment. Our data provides a spatial atlas of melanoma LMD, identifies the tumor-promoting role of meningeal stroma, and demonstrates a mechanism for overcoming microenvironment-mediated drug resistance unique to this metastatic site.

CDK4/6 inhibition synergizes with inhibition of P21-Activated Kinases (PAKs) in lung cancer cell lines.

Theoretically, small molecule CDK4/6 inhibitors (CDK4/6is) represent a logical therapeutic option in non-small cell lung cancers since most of these malignancies have wildtype RB, the key target of CDKs and master regulator of the cell cycle. Unfortunately, CDK4/6is are found to have limited clinical activity as single agents in non-small cell lung cancer. To address this problem and to identify effective CDK4/6i combinations, we screened a library of targeted agents for efficacy in four non-small cell lung cancer lines treated with CDK4/6 inhibitors Palbociclib or Abemaciclib. The pan-PAK (p21-activated kinase) inhibitor PF03758309 emerged as a promising candidate with viability ratios indicating synergy in all 4 cell lines and for both CDK4/6is. It is noteworthy that the PAKs are downstream effectors of small GTPases Rac1 and Cdc42 and are overexpressed in a wide variety of cancers. Individually the compounds primarily induced cell cycle arrest; however, the synergistic combination induced apoptosis, accounting for the synergy. Surprisingly, while the pan-PAK inhibitor PF03758309 synergizes with CDK4/6is, no synergy occurs with group I PAK inhibitors FRAX486 or FRAX597. Cell lines treated only with Ribociclib, FRAX486 or FRAX597 underwent G1/G0 arrest, whereas combination treatment with these compounds predominantly resulted in autophagy. Combining high concentrations of FRAX486, which weakly inhibits PAK4, and Ribociclib, mimics the autophagy and apoptotic effect of PF03758309 combined with Ribociclib. FRAX597, a PAKi that does not inhibit PAK4 did not reduce autophagy in combination with Ribociclib. Our results suggest that a unique combination of PAKs plays a crucial role in the synergy of PAK inhibitors with CDK4/6i. Targeting this unique PAK combination, could greatly improve the efficacy of CDK4/6i and broaden the spectrum of cancer treatment.

Loss of cellular identity in common pre-clinical models of serine­threonine kinase 11 (Liver kinase B1) loss.

Nearly 1/3 of lung adenocarcinomas have loss of STK11 (LKB1) function. Herein, a bioinformatics approach was used to determine how accurately preclinical model systems reflect the in vivo biology of STK11 loss in human patients. Hierarchical and K-mean clustering, principle component, and gene set enrichment analyses were employed to model gene expression due to STK11 loss in patient cohorts representing nearly 1000 lung adenocarcinoma patients. K-means clustering classified STK11 loss patient tumors into three distinct sub-groups; positive (54%), neuroendocrine (NE) (35%) and negative (11%). The positive and NE groups are both defined by the expression of NKX2-1. In addition to NKX2-1, NE patients express neuroendocrine markers such as ASCL1 and CALCA. In contrast, the negative group does not express NKX2-1 (or neuroendocrine markers) and is characterized by significantly reduced survival relative to the two other groups. Two gene expression signatures were derived to explain both neuroendocrine features and differentiation (NKX2-1 loss) and were validated through two public datasets involving chemical differentiation (DCI) and NKX2-1 reconstitution. Patients results were then compared with established cell lines, transgenic mice, and patient-derived xenograft models of STK11 loss. Interestingly, all cell line and PDX models cluster and show expression patterns similar with the NKX2-1 negative subset of STK11-loss human tumors. Surprisingly, even mouse models of STK11 loss do not resemble patient tumors based on gene expression patterns. Results suggest pre-clinical models of STK11 loss are pronounced by marked elimination of type II pneumocyte identity, opposite of most in vivo human tumors.

MEK Inhibition Modulates Cytokine Response to Mediate Therapeutic Efficacy in Lung Cancer.

Activating mutations in BRAF, a key mediator of RAS signaling, are present in approximately 50% of melanoma patients. Pharmacologic inhibition of BRAF or the downstream MAP kinase MEK is highly effective in treating BRAF-mutant melanoma. In contrast, RAS pathway inhibitors have been less effective in treating epithelial malignancies, such as lung cancer. Here, we show that treatment of melanoma patients with BRAF and MEK inhibitors (MEKi) activated tumor NF-κB activity. MEKi potentiated the response to TNFα, a potent activator of NF-κB. In both melanoma and lung cancer cells, MEKi increased cell-surface expression of TNFα receptor 1 (TNFR1), which enhanced NF-κB activation and augmented expression of genes regulated by TNFα and IFNγ. Screening of 289 targeted agents for the ability to increase TNFα and IFNγ target gene expression demonstrated that this was a general activity of inhibitors of MEK and ERK kinases. Treatment with MEKi led to acquisition of a novel vulnerability to TNFα and IFNγ-induced apoptosis in lung cancer cells that were refractory to MEKi killing and augmented cell-cycle arrest. Abolishing the expression of TNFR1 on lung cancer cells impaired the antitumor efficacy of MEKi, whereas the administration of TNFα and IFNγ in MEKi-treated mice enhanced the antitumor response. Furthermore, immunotherapeutics known to induce expression of these cytokines synergized with MEKi in eradicating tumors. These findings define a novel cytokine response modulatory function of MEKi that can be therapeutically exploited. SIGNIFICANCE: Lung cancer cells are rendered sensitive to MEK inhibitors by TNFα and IFNγ, providing a strong mechanistic rationale for combining immunotherapeutics, such as checkpoint blockers, with MEK inhibitor therapy for lung cancer.See related commentary by Havel, p. 5699.

Hyper-phosphorylation of Rb S249 together with CDK5R2/p39 overexpression are associated with impaired cell adhesion and epithelial-to-mesenchymal transition: Implications as a potential lung cancer grading and staging biomarker.

Prediction of lung cancer metastasis relies on post-resection assessment of tumor histology, which is a severe limitation since only a minority of lung cancer patients are diagnosed with resectable disease. Therefore, characterization of metastasis-predicting biomarkers in pre-resection small biopsy specimens is urgently needed. Here we report a biomarker consisting of the phosphorylation of the retinoblastoma protein (Rb) on serine 249 combined with elevated p39 expression. This biomarker correlates with epithelial-to-mesenchymal transition traits in non-small cell lung carcinoma (NSCLC) cells. Immunohistochemistry staining of NSCLC tumor microarrays showed that strong phospho-Rb S249 staining positively correlated with tumor grade specifically in the squamous cell carcinoma (SCC) subtype. Strong immunoreactivity for p39 positively correlated with tumor stage, lymph node invasion, and distant metastases, also in SCC. Linear regression analyses showed that the combined scoring for phospho-Rb S249, p39 and E-cadherin in SCC is even more accurate at predicting tumor staging, relative to each score individually. We propose that combined immunohistochemistry staining of NSCLC samples for Rb phosphorylation on S249, p39, and E-cadherin protein expression could aid in the assessment of tumor staging and metastatic potential when tested in small primary tumor biopsies. The intense staining for phospho-Rb S249 that we observed in high grade SCC could also aid in the precise sub-classification of poorly differentiated SCCs.

Somatic Mutations and Ancestry Markers in Hispanic Lung Cancer Patients.

INTRODUCTION: To address the lack of genomic data from Hispanic/Latino (H/L) patients with lung cancer, the Latino Lung Cancer Registry was established to collect patient data and biospecimens from H/L patients. METHODS: This retrospective observational study examined lung cancer tumor samples from 163 H/L patients, and tumor-derived DNA was subjected to targeted-exome sequencing (>1000 genes, including EGFR, KRAS, serine/threonine kinase 11 gene [STK11], and tumor protein p53 gene [TP53]) and ancestry analysis. Mutation frequencies in this H/L cohort were compared with those in a similar cohort of non-Hispanic white (NHW) patients and correlated with ancestry, sex, smoking status, and tumor histologic type. RESULTS: Of the adenocarcinomas in the H/L cohort (n = 120), 31% had EGFR mutations, versus 17% in the NHW control group (p < 0.001). KRAS (20% versus 38% [p = 0.002]) and STK11 (8% versus 16% [p = 0.065]) mutations occurred at lower frequency, and mutations in TP53 occurred at similar frequency (46% versus 40% [p = 0.355]) in H/L and NHW patients, respectively. Within the Hispanic cohort, ancestry influenced the rate of TP53 mutations (p = 0.009) and may have influenced the rate of EGFR, KRAS, and STK11 mutations. CONCLUSIONS: Driver mutations in H/L patients with lung adenocarcinoma differ in frequency from those in NHW patients associated with their indigenous American ancestry. The spectrum of driver mutations needs to be further assessed in the H/L population.

Evaluating somatic tumor mutation detection without matched normal samples.

BACKGROUND: Observations of recurrent somatic mutations in tumors have led to identification and definition of signaling and other pathways that are important for cancer progression and therapeutic targeting. As tumor cells contain both an individual's inherited genetic variants and somatic mutations, challenges arise in distinguishing these events in massively parallel sequencing datasets. Typically, both a tumor sample and a "normal" sample from the same individual are sequenced and compared; variants observed only in the tumor are considered to be somatic mutations. However, this approach requires two samples for each individual. RESULTS: We evaluate a method of detecting somatic mutations in tumor samples for which only a subset of normal samples are available. We describe tuning of the method for detection of mutations in tumors, filtering to remove inherited variants, and comparison of detected mutations to several matched tumor/normal analysis methods. Filtering steps include the use of population variation datasets to remove inherited variants as well a subset of normal samples to remove technical artifacts. We then directly compare mutation detection with tumor-only and tumor-normal approaches using the same sets of samples. Comparisons are performed using an internal targeted gene sequencing dataset (n = 3380) as well as whole exome sequencing data from The Cancer Genome Atlas project (n = 250). Tumor-only mutation detection shows similar recall (43-60%) but lesser precision (20-21%) to current matched tumor/normal approaches (recall 43-73%, precision 30-82%) when compared to a "gold-standard" tumor/normal approach. The inclusion of a small pool of normal samples improves precision, although many variants are still uniquely detected in the tumor-only analysis. CONCLUSIONS: A detailed method for somatic mutation detection without matched normal samples enables study of larger numbers of tumor samples, as well as tumor samples for which a matched normal is not available. As sensitivity/recall is similar to tumor/normal mutation detection but precision is lower, tumor-only detection is more appropriate for classification of samples based on known mutations. Although matched tumor-normal analysis is preferred due to higher precision, we demonstrate that mutation detection without matched normal samples is possible for certain applications.

Expression and alternative splicing of the cyclin-dependent kinase inhibitor-3 gene in human cancer.

The cyclin-dependent kinase inhibitor-3 (CDKN3) gene encodes a dual-specificity protein tyrosine phosphatase that dephosphorylates CDK1/CDK2 and other proteins. CDKN3 is often overexpressed in human cancer, and this overexpression correlates with reduced survival in several types of cancer. CDKN3 transcript variants and mutations have also been reported. The mechanism of CDKN3 overexpression and the role of CDKN3 transcript variants in human cancer are not entirely clear. Here, we review the literature and provide additional data to assess the correlation of CDKN3 expression with patient survival. Besides the full-length CDKN3 encoding transcript and a major transcript that skips exon 2 express in normal and cancer cells, minor aberrant transcript variants have been reported. Aberrant CDKN3 transcripts were postulated to encode dominant-negative inhibitors of CDKN3 as an explanation for overexpression of the perceived tumor suppressor gene in human cancer. However, while CDKN3 is often overexpressed in human cancer, aberrant CDKN3 transcripts occur infrequently and at lower levels. CDKN3 mutations and copy number alternation are rare in human cancer, implying that neither loss of CDKN3 activity nor constitutive gain of CDKN3 expression offer an advantage to tumorigenesis. Recently, it was found that CDKN3 transcript and protein levels fluctuate during the cell cycle, peaking in mitosis. Given that rapidly growing tumors have more mitotic cells, the high level of mitotic CDKN3 expression is the most plausible mechanism of frequent CDKN3 overexpression in human cancer. This finding clarifies the mechanism of CDKN3 overexpression in human cancer and questions the view of CDKN3 as a tumor suppressor.

Early2 factor (E2F) deregulation is a prognostic and predictive biomarker in lung adenocarcinoma.

Clinicians routinely prescribe adjuvant chemotherapy (ACT) for resected non-small cell lung cancer patients. However, ACT only improves five-year disease-free survival in stage I-III non-small cell lung cancer by 5-15%, with most patients deriving no benefit. Herein, deregulation of the E2F pathway was explored as a biomarker in lung adenocarcinoma patients. An E2F pathway scoring system, based on 74 E2F-regulated genes, was trained for RNA from two platforms: fresh-frozen (FF) or formalin-fixed paraffin-embedded (FFPE) tissues. The E2F score was tested as a prognostic biomarker in five FF-based cohorts and two FFPE-based cohorts. The E2F score was tested as a predictive biomarker in two randomized clinical trials; JBR10 and the NATCH (Neo-Adjuvant Taxol-Carboplatin Hope) trial. The E2F score was prognostic in untreated patients in all seven datasets examined (p < 0.05). Stage-specific analysis of combined cohorts demonstrated that the E2F score was prognostic in stage I patients (p = 0.0495 to <0.001; hazard ratio, HR, =2.04- 2.22) with a similar trend in other stages. The E2F score was strongly predictive in stage II patients from the two combined randomized clinical trials with a significant differential treatment effect (p = 0.015). Specifically, ACT improved survival in stage II patients with high E2F (p = 0.01; HR= 0.21). The 5-year survival increased from 18% to 81%. In contrast, in patients with low E2F, 5-year survival was 57% in untreated patients and 41% in ACT-treated patients with a HR of 1.55 (p = 0.47). In summary, the E2F score provides valuable prognostic information for Stage I and predictive information for Stage II lung adenocarcinoma patients and should be further explored as a decision support tool for their treatment.

Strategies for power calculations in predictive biomarker studies in survival data.

PURPOSE: Biomarkers and genomic signatures represent potentially predictive tools for precision medicine. Validation of predictive biomarkers in prospective or retrospective studies requires statistical justification of power and sample size. However, the design of these studies is complex and the statistical methods and associated software are limited, especially in survival data. Herein, we address common statistical design issues relevant to these two types of studies and provide guidance and a general template for analysis. METHODS: A statistical interaction effect in the Cox proportional hazards model is used to describe predictive biomarkers. The analytic form by Peterson et al. and Lachin is utilized to calculate the statistical power for both prospective and retrospective studies. RESULTS: We demonstrate that the common mistake of using only Hazard Ratio's Ratio (HRR) or two hazard ratios (HRs) can mislead power calculations. We establish that the appropriate parameter settings for prospective studies require median survival time (MST) in 4 subgroups (treatment and control in positive biomarker, treatment and control in negative biomarker). For the retrospective study which has fixed survival time and censored status, we develop a strategy to harmonize the hypothesized parameters and the study cohort. Moreover, we provide an easily-adapted R software application to generate a template of statistical plan for predictive biomarker validation so investigators can easily incorporate into their study proposals. CONCLUSION: Our study provides guidance and software to help biostatisticians and clinicians design sound clinical studies for testing predictive biomarkers.

PAXIP1 Potentiates the Combination of WEE1 Inhibitor AZD1775 and Platinum Agents in Lung Cancer.

The DNA damage response (DDR) involves a complex network of signaling events mediated by modular protein domains such as the BRCA1 C-terminal (BRCT) domain. Thus, proteins that interact with BRCT domains and are a part of the DDR constitute potential targets for sensitization to DNA-damaging chemotherapy agents. We performed a pharmacologic screen to evaluate 17 kinases, identified in a BRCT-mediated interaction network as targets to enhance platinum-based chemotherapy in lung cancer. Inhibition of mitotic kinase WEE1 was found to have the most effective response in combination with platinum compounds in lung cancer cell lines. In the BRCT-mediated interaction network, WEE1 was found in complex with PAXIP1, a protein containing six BRCT domains involved in transcription and in the cellular response to DNA damage. We show that PAXIP1 BRCT domains regulate WEE1-mediated phosphorylation of CDK1. Furthermore, ectopic expression of PAXIP1 promotes enhanced caspase-3-mediated apoptosis in cells treated with WEE1 inhibitor AZD1775 (formerly, MK-1775) and cisplatin compared with cells treated with AZD1775 alone. Cell lines and patient-derived xenograft models expressing both PAXIP1 and WEE1 exhibited synergistic effects of AZD1775 and cisplatin. In summary, PAXIP1 is involved in sensitizing lung cancer cells to the WEE1 inhibitor AZD1775 in combination with platinum-based treatment. We propose that WEE1 and PAXIP1 levels may be used as mechanism-based biomarkers of response when WEE1 inhibitor AZD1775 is combined with DNA-damaging agents. Mol Cancer Ther; 15(7); 1669-81. ©2016 AACR.

cAMP/CREB-regulated LINC00473 marks LKB1-inactivated lung cancer and mediates tumor growth.

The LKB1 tumor suppressor gene is frequently mutated and inactivated in non-small cell lung cancer (NSCLC). Loss of LKB1 promotes cancer progression and influences therapeutic responses in preclinical studies; however, specific targeted therapies for lung cancer with LKB1 inactivation are currently unavailable. Here, we have identified a long noncoding RNA (lncRNA) signature that is associated with the loss of LKB1 function. We discovered that LINC00473 is consistently the most highly induced gene in LKB1-inactivated human primary NSCLC samples and derived cell lines. Elevated LINC00473 expression correlated with poor prognosis, and sustained LINC00473 expression was required for the growth and survival of LKB1-inactivated NSCLC cells. Mechanistically, LINC00473 was induced by LKB1 inactivation and subsequent cyclic AMP-responsive element-binding protein (CREB)/CREB-regulated transcription coactivator (CRTC) activation. We determined that LINC00473 is a nuclear lncRNA and interacts with NONO, a component of the cAMP signaling pathway, thereby facilitating CRTC/CREB-mediated transcription. Collectively, our study demonstrates that LINC00473 expression potentially serves as a robust biomarker for tumor LKB1 functional status that can be integrated into clinical trials for patient selection and treatment evaluation, and implicates LINC00473 as a therapeutic target for LKB1-inactivated NSCLC.

A Sensitive NanoString-Based Assay to Score STK11 (LKB1) Pathway Disruption in Lung Adenocarcinoma.

INTRODUCTION: Serine/threonine kinase 11 gene (STK11), better known as liver kinase ß1, is a tumor suppressor that is commonly mutated in lung adenocarcinoma (LUAD). Previous work has shown that mutational inactivation of the STK11 pathway may serve as a predictive biomarker for cancer treatments, including phenformin and cyclooxygenase-2 inhibition. Although immunohistochemical (IHC) staining and diagnostic sequencing are used to measure STK11 pathway disruption, there are serious limitations to these methods, thus emphasizing the importance of validating a clinically useful assay. METHODS: An initial STK11 mutation mRNA signature was generated using cell line data and refined using three large, independent patient databases. The signature was validated as a classifier using The Cancer Genome Atlas (TCGA) LUAD cohort as well as a 442-patient LUAD cohort developed at Moffitt. Finally, the signature was adapted to a NanoString-based format and validated using RNA samples isolated from formalin-fixed, paraffin-embedded tissue blocks corresponding to a cohort of 150 patients with LUAD. For comparison, STK11 IHC staining was also performed. RESULTS: The STK11 signature was found to correlate with null mutations identified by exon sequencing in multiple cohorts using both microarray and NanoString formats. Although there was a statistically significant correlation between reduced STK11 protein expression by IHC staining and mutation status, the NanoString-based assay showed superior overall performance, with a -0.1588 improvement in area under the curve in receiver-operator characteristic curve analysis (p < 0.012). CONCLUSION: The described NanoString-based STK11 assay is a sensitive biomarker to study emerging therapeutic modalities in clinical trials.

The Retinoblastoma Tumor Suppressor Transcriptionally Represses Pak1 in Osteoblasts.

We previously characterized the retinoblastoma tumor suppressor protein (Rb) as a regulator of adherens junction assembly and cell-to-cell adhesion in osteoblasts. This is a novel function since Rb is predominantly known as a cell cycle repressor. Herein, we characterized the molecular mechanisms by which Rb performs this function, hypothesizing that Rb controls the activity of known regulators of adherens junction assembly. We found that Rb represses the expression of the p21-activated protein kinase (Pak1), an effector of the small Rho GTPase Rac1. Rac1 is a well-known regulator of adherens junction assembly whose increased activity in cancer is linked to perturbations of intercellular adhesion. Using nuclear run-on and luciferase reporter transcription assays, we found that Pak1 repression by Rb is transcriptional, without affecting Pak1 mRNA and protein stability. Pak1 promoter bioinformatics showed multiple E2F1 binding sites within 155 base pairs of the transcriptional start site, and a Pak1-promoter region containing these E2F sites is susceptible to transcriptional inhibition by Rb. Chromatin immunoprecipitations showed that an Rb-E2F complex binds to the region of the Pak1 promoter containing the E2F1 binding sites, suggesting that Pak1 is an E2F target and that the repressive effect of Rb on Pak1 involves blocking the trans-activating capacity of E2F. A bioinformatics analysis showed elevated Pak1 expression in several solid tumors relative to adjacent normal tissue, with both Pak1 and E2F increased relative to normal tissue in breast cancer, supporting a cancer etiology for Pak1 up-regulation. Therefore, we propose that by repressing Pak1 expression, Rb prevents Rac1 hyperactivity usually associated with cancer and related to cytoskeletal derangements that disrupt cell adhesion, consequently enhancing cancer cell migratory capacity. This de-regulation of cell adhesion due to Rb loss could be part of the molecular events associated with cancer progression and metastasis.

Overexpression of major CDKN3 transcripts is associated with poor survival in lung adenocarcinoma.

BACKGROUND: The cyclin-dependent kinase inhibitor 3 (CDKN3) has been perceived as a tumour suppressor. Paradoxically, CDKN3 is often overexpressed in human cancer. It was unclear if CDKN3 overexpression is linked to alternative splicing variants or mutations that produce dominant-negative CDKN3. METHODS: We analysed CDKN3 expression and its association with patient survival in three cohorts of lung adenocarcinoma. We also examined CDKN3 mutations in the Cancer Genome Atlas (TCGA) and the Moffitt Cancer Center's Total Cancer Care (TCC) projects. CDKN3 transcripts were further analysed in a panel of cell lines and lung adenocarcinoma tissues. CDKN3 mRNA and protein levels in different cell cycle phases were examined. RESULTS: CDKN3 is overexpressed in non small cell lung cancer. High CDKN3 expression is associated with poor overall survival in lung adenocarcinoma. Two CDKN3 transcripts were detected in all samples. These CDKN3 transcripts represent the full length CDKN3 mRNA and a normal transcript lacking exon 2, which encodes an out of frame 23-amino acid peptide with little homology to CDKN3. CDKN3 mutations were found to be very rare. CDKN3 mRNA and protein were elevated during the mitosis phase of cell cycle. CONCLUSIONS: CDKN3 overexpression is prognostic of poor overall survival in lung adenocarcinoma. CDKN3 overexpression in lung adenocarcinoma is not attributed to alternative splicing or mutation but is likely due to increased mitotic activity, arguing against CDKN3 as a tumour suppressor.

Functional signaling pathway analysis of lung adenocarcinomas identifies novel therapeutic targets for KRAS mutant tumors.

Little is known about the complex signaling architecture of KRAS and the interconnected RAS-driven protein-protein interactions, especially as it occurs in human clinical specimens. This study explored the activated and interconnected signaling network of KRAS mutant lung adenocarcinomas (AD) to identify novel therapeutic targets.Thirty-four KRAS mutant (MT) and twenty-four KRAS wild-type (WT) frozen biospecimens were obtained from surgically treated lung ADs. Samples were subjected to Laser Capture Microdissection and Reverse Phase Protein Microarray analysis to explore the expression/activation levels of 150 signaling proteins along with co-activation concordance mapping. An independent set of 90 non-small cell lung cancers (NSCLC) was used to validate selected findings by immunohistochemistry (IHC).Compared to KRAS WT tumors, the signaling architecture of KRAS MT ADs revealed significant interactions between KRAS downstream substrates, the AKT/mTOR pathway, and a number of Receptor Tyrosine Kinases (RTK). Approximately one-third of the KRAS MT tumors had ERK activation greater than the WT counterpart (p<0.01). Notably 18% of the KRAS MT tumors had elevated activation of the Estrogen Receptor alpha (ER-α) (p=0.02).This finding was verified in an independent population by IHC (p=0.03).KRAS MT lung ADs appear to have a more intricate RAS linked signaling network than WT tumors with linkage to many RTKs and to the AKT-mTOR pathway. Combination therapy targeting different nodes of this network may be necessary to treat this group of patients. In addition, for patients with KRAS MT tumors and activation of the ER-α, anti-estrogen therapy may have important clinical implications.