B cell-dependent subtypes and treatment-based immune correlates to survival in stage 3 and 4 lung adenocarcinomas.

Lung cancer is the leading cause of cancer-related deaths worldwide. Surgery and chemoradiation are the standard of care in early stages of non-small cell lung cancer (NSCLC), while immunotherapy is the standard of care in late-stage NSCLC. The immune composition of the tumor microenvironment (TME) is recognized as an indicator for responsiveness to immunotherapy, although much remains unknown about its role in responsiveness to surgery or chemoradiation. In this pilot study, we characterized the NSCLC TME using mass cytometry (CyTOF) and bulk RNA sequencing (RNA-Seq) with deconvolution of RNA-Seq being performed by Kassandra, a recently published deconvolution tool. Stratification of patients based on the intratumoral abundance of B cells identified that the B-cell rich patient group had increased expression of CXCL13 and greater abundance of PD1+ CD8 T cells. The presence of B cells and PD1+ CD8 T cells correlated positively with the presence of intratumoral tertiary lymphoid structures (TLS). We then assessed the predictive and prognostic utility of these cell types and TLS within publicly available stage 3 and 4 lung adenocarcinoma (LUAD) RNA-Seq datasets. As previously described by others, pre-treatment expression of intratumoral 12-chemokine TLS gene signature is associated with progression free survival (PFS) in patients who receive treatment with immune checkpoint inhibitors (ICI). Notably and unexpectedly pre-treatment percentages of intratumoral B cells are associated with PFS in patients who receive surgery, chemotherapy, or radiation. Further studies to confirm these findings would allow for more effective patient selection for both ICI and non-ICI treatments.

Multiregional single-cell proteogenomic analysis of ccRCC reveals cytokine drivers of intratumor spatial heterogeneity.

Intratumor heterogeneity (ITH) represents a major challenge for anticancer therapies. An integrated, multidimensional, multiregional approach dissecting ITH of the clear cell renal cell carcinoma (ccRCC) tumor microenvironment (TME) is employed at the single-cell level with mass cytometry (CyTOF), multiplex immunofluorescence (MxIF), and single-nucleus RNA sequencing (snRNA-seq) and at the bulk level with whole-exome sequencing (WES), RNA-seq, and methylation profiling. Multiregional analyses reveal unexpected conservation of immune composition within each individual patient, with profound differences among patients, presenting patient-specific tumor immune microenvironment signatures despite underlying genetic heterogeneity from clonal evolution. Spatial proteogenomic TME analysis using MxIF identifies 14 distinct cellular neighborhoods and, conversely, demonstrated architectural heterogeneity among different tumor regions. Tumor-expressed cytokines are identified as key determinants of the TME and correlate with clinical outcome. Overall, this work signifies that spatial ITH occurs in ccRCC, which may drive clinical heterogeneity and warrants further interrogation to improve patient outcomes.

Diagnostic Utility of RNA-Seq for Evaluation of PD-L1 Expression in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Although there are immune checkpoint inhibitors (ICIs) available for the treatment of renal cell carcinoma (RCC), the utility of PD-L1 detection by immunohistochemistry (IHC) as a predictive biomarker in clear cell RCC (ccRCC) remains controversial. Nevertheless, alternative methods for PD-L1 detection, such as RNA sequencing (RNA-Seq), may be clinically useful in ccRCC; therefore, we sought to determine the ability of RNA-Seq to accurately and sensitively detect PD-L1 expression across different ccRCC clinical samples in comparison with IHC. PATIENTS AND METHODS: Patients with ccRCC (n=127) who received treatment from Washington University in St. Louis between 2018 and 2020 were identified. Tumors from these patients were analyzed using RNA-Seq and IHC. RESULTS: PD-L1 detection by RNA-Seq strongly correlated with IHC (P < .001), which was further validated using two independent datasets. Furthermore, RNA-Seq analysis identified an immune-enriched (higher PD-L1 positivity) and an immune-desert (lower PD-L1 positivity) microenvironment of ccRCC, which also correlated with IHC (P < .00001). CONCLUSION: The results demonstrate the ability of RNA-Seq to detect PD-L1 in various ccRCC clinical samples compared to IHC. Ultimately, these findings suggest that PD-L1 detection by RNA-Seq can be further developed to determine the clinical utility of this methodology in ccRCC.

Conserved pan-cancer microenvironment subtypes predict response to immunotherapy.

The clinical use of molecular targeted therapy is rapidly evolving but has primarily focused on genomic alterations. Transcriptomic analysis offers an opportunity to dissect the complexity of tumors, including the tumor microenvironment (TME), a crucial mediator of cancer progression and therapeutic outcome. TME classification by transcriptomic analysis of >10,000 cancer patients identifies four distinct TME subtypes conserved across 20 different cancers. The TME subtypes correlate with patient response to immunotherapy in multiple cancers, with patients possessing immune-favorable TME subtypes benefiting the most from immunotherapy. Thus, the TME subtypes act as a generalized immunotherapy biomarker across many cancer types due to the inclusion of malignant and microenvironment components. A visual tool integrating transcriptomic and genomic data provides a global tumor portrait, describing the tumor framework, mutational load, immune composition, anti-tumor immunity, and immunosuppressive escape mechanisms. Integrative analyses plus visualization may aid in biomarker discovery and the personalization of therapeutic regimens.

Single-cell Spatial Proteomic Revelations on the Multiparametric MRI Heterogeneity of Clinically Significant Prostate Cancer.

PURPOSE: Multiparametric MRI (mpMRI) has become an indispensable radiographic tool in diagnosing prostate cancer. However, mpMRI fails to visualize approximately 15% of clinically significant prostate cancer (csPCa). The molecular, cellular, and spatial underpinnings of such radiographic heterogeneity in csPCa are unclear. EXPERIMENTAL DESIGN: We examined tumor tissues from clinically matched patients with mpMRI-invisible and mpMRI-visible csPCa who underwent radical prostatectomy. Multiplex immunofluorescence single-cell spatial imaging and gene expression profiling were performed. Artificial intelligence-based analytic algorithms were developed to examine the tumor ecosystem and integrate with corresponding transcriptomics. RESULTS: More complex and compact epithelial tumor architectures were found in mpMRI-visible than in mpMRI-invisible prostate cancer tumors. In contrast, similar stromal patterns were detected between mpMRI-invisible prostate cancer and normal prostate tissues. Furthermore, quantification of immune cell composition and tumor-immune interactions demonstrated a lack of immune cell infiltration in the malignant but not in the adjacent nonmalignant tissue compartments, irrespective of mpMRI visibility. No significant difference in immune profiles was detected between mpMRI-visible and mpMRI-invisible prostate cancer within our patient cohort, whereas expression profiling identified a 24-gene stromal signature enriched in mpMRI-invisible prostate cancer. Prostate cancer with strong stromal signature exhibited a favorable survival outcome within The Cancer Genome Atlas prostate cancer cohort. Notably, five recurrences in the 8 mpMRI-visible patients with csPCa and no recurrence in the 8 clinically matched patients with mpMRI-invisible csPCa occurred during the 5-year follow-up post-prostatectomy. CONCLUSIONS: Our study identified distinct molecular, cellular, and structural characteristics associated with mpMRI-visible csPCa, whereas mpMRI-invisible tumors were similar to normal prostate tissue, likely contributing to mpMRI invisibility.

Clinical and Biological Subtypes of B-cell Lymphoma Revealed by Microenvironmental Signatures.

Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogeneous disease. Transcriptomic and genetic characterization of DLBCL has increased the understanding of its intrinsic pathogenesis and provided potential therapeutic targets. However, the role of the microenvironment in DLBCL biology remains less understood. Here, we performed a transcriptomic analysis of the microenvironment of 4,655 DLBCLs from multiple independent cohorts and described four major lymphoma microenvironment categories that associate with distinct biological aberrations and clinical behavior. We also found evidence of genetic and epigenetic mechanisms deployed by cancer cells to evade microenvironmental constraints of lymphoma growth, supporting the rationale for implementing DNA hypomethylating agents in selected patients with DLBCL. In addition, our work uncovered new therapeutic vulnerabilities in the biochemical composition of the extracellular matrix that were exploited to decrease DLBCL proliferation in preclinical models. This novel classification provides a road map for the biological characterization and therapeutic exploitation of the DLBCL microenvironment. SIGNIFICANCE: In a translational relevant transcriptomic-based classification, we characterized the microenvironment as a critical component of the B-cell lymphoma biology and associated it with the DLBCL clinical behavior establishing a novel opportunity for targeting therapies.This article is highlighted in the In This Issue feature, p. 1307.

Phenotypic profiling of Raf inhibitors and mitochondrial toxicity in 3D tissue using biodynamic imaging.

The existence of phenotypic differences in the drug responses of 3D tissue relative to 2D cell culture is a concern in high-content drug screening. Biodynamic imaging is an emerging technology that probes 3D tissue using short-coherence dynamic light scattering to measure the intracellular motions inside tissues in their natural microenvironments. The information content of biodynamic imaging is displayed through tissue dynamics spectroscopy (TDS) but has not previously been correlated against morphological image analysis of 2D cell culture. In this article, a set of mitochondria-affecting compounds (FCCP, valinomycin, nicardipine, ionomycin) and Raf kinase inhibitors (PLX4032, PLX4720, GDC, and sorafenib) are applied to multicellular tumor spheroids from two colon adenocarcinoma cell lines (HT-29 and DLD-1). These were screened by TDS and then compared against conventional image-based high-content analysis (HCA). The responses to the Raf inhibitors PLX4032 and PLX4720 are grouped separately by cell line, reflecting the Braf/Kras difference in these cell lines. There is a correlation between TDS and HCA phenotypic clustering for most cases, which demonstrates the ability of dynamic measurements to capture phenotypic responses to drugs. However, there are significant 2D versus 3D phenotypic differences exhibited by several of the drugs/cell lines.

Differential mitochondrial toxicity screening and multi-parametric data analysis.

Early evaluation of new drug entities for their potential to cause mitochondrial dysfunction is becoming an important task for drug development. Multi-parametric high-content screening (mp-HCS) of mitochondrial toxicity holds promise as a lead in-vitro strategy for drug testing and safety evaluations. In this study, we have developed a mp-HCS and multi-parametric data analysis scheme for assessing cell responses to induced mitochondrial perturbation. The mp-HCS measurements are shown to be robust enough to allow for quantitative comparison of biological systems with different metabolic pathways simulated by alteration of growth media. Substitution of medium glucose for galactose sensitized cells to drug action and revealed novel response parameters. Each compound was quantitatively characterized according to induced phenotypic changes of cell morphology and functionality measured by fluorescent biomarkers for mitochondrial activity, plasma membrane permeability, and nuclear morphology. Descriptors of drug effects were established by generation of a SCRIT (Specialized-Cell-Response-to-Induced-Toxicity) vector, consisting of normalized statistical measures of each parameter at each dose and growth condition. The dimensionality of SCRIT vectors depends on the number of parameters chosen, which in turn depends on the hypothesis being tested. Specifically, incorporation of three parameters of response into SCRIT vectors enabled clustering of 84 training compounds with known pharmacological and toxicological activities according to the degree of toxicity and mitochondrial involvement. Inclusion of 6 parameters enabled the resolution of more subtle differences between compounds within a common therapeutic class; scoring enabled a ranking of statins in direct agreement with clinical outcomes. Comparison of drug-induced changes required variations in glucose for separation of mitochondrial dysfunction from other types of cytotoxicity. These results also demonstrate that the number of drugs in a training set, the choice of parameters used in analysis, and statistical measures are fundamental for specific hypothesis testing and assessment of quantitative phenotypic differences.

Selection of peptides binding to the amyloid b-protein reveals potential inhibitors of amyloid formation.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by extracellular amyloid plaques, cerebrovascular amyloid deposits, intracellular neurofibrillary tangles, and neuronal loss. Amyloid deposits are composed of insoluble fibers of a 39-43 amino acid peptide named the amyloid beta-protein (A beta). Neuropathological and genetic studies provide strong evidence of a key role for A beta amyloidosis in the pathogenesis of AD. Therefore, an obvious pharmacological target for treatment of AD is the inhibition of amyloid growth and/or inhibition of amyloid function. We took an unbiased approach to generate new inhibitors of amyloid formation by screening a FliTrx combinatorial peptide library for A beta binding peptides and identified four groups of peptides with different A beta binding motifs. In addition, we designed and examined peptides mimicking the A beta binding domain of transthyretin (TTR). Our results showed that A beta binding peptides selected from FliTrx peptide library and from TTR-peptide analogs are capable of inhibiting A beta aggregation and A beta deposition in vitro. These properties demonstrate that binding of selected peptides to the amyloid beta-protein may provide potent therapeutic compounds for the treatment AD.

Amyloidogenic and anti-amyloidogenic properties of recombinant transthyretin variants.

Most transthyretin (TTR) mutations lead to TTR amyloid depositions in patients with familial amyloidotic polyneuropathy and familial amyloidotic cardiomyopathy. However, though an amyloidogenic protein itself, TTR inhibits aggregation of Alzheimer's amyloid beta protein (A beta) in vitro and in vivo. The pathogenic relationship between two amyloidogenic processes remains unclear. To understand how TTR mutations influence the ability of TTR to inhibit A beta amyloidosis, forty-seven recombinant TTR variants were produced and analyzed. We showed that all recombinant proteins formed tetramers and were functional in thyroxine binding. Acid denaturation at pH 3.8 resulted in aggregation and fibril formation of all TTR variants. However, only TTR G42 and TTR P55 formed fibrils at pH 6.8. Most TTR variants bound to A beta and inhibited A beta aggregation in vitro. TTR variants S64, A71, Q89, V107, H114 and I122 revealed decreased binding to A beta and decreased inhibition of A beta aggregation. Only TTR G42 and TTR P55 completely failed to bind A beta and to inhibit A beta aggregation. We suggest that TTR variants characterized by decreased binding to A beta or by decreased inhibition of A beta aggregation in vitro may contribute to A beta amyloid formation in vivo. These TTR variants might be important targets for epidemiological studies in Alzheimer's disease.

Laminin assembles into separate basement membrane and fibrillar matrices in Schwann cells.

Laminins are important for Schwann cell basement membrane assembly and axonal function. In this study, we found that exogenous laminin-1, like neuromuscular laminins-2/4, formed two distinct extracellular matrices on Schwann cell surfaces, each facilitated by laminin polymerization. Assembly of one, a densely-distributed reticular matrix, was accompanied by a redistribution of cell-surface dystroglycan and cytoskeletal utrophin into matrix-receptor-cytoskeletal complexes. The other, a fibrillar matrix, accumulated in separate zones associated with pre-existing beta1-integrin arrays. The laminin-1 fragment E3 (LG-modules 4-5), which binds dystroglycan and heparin, inhibited reticular-matrix formation. By contrast, beta1-integrin blocking antibody (Ha2/5) prevented fibrillar assembly. Ultrastructural analysis revealed that laminin treatment induced the formation of a linear electron-dense extracellular matrix (lamina densa) separated from plasma membrane by a narrow lucent zone (lamina lucida). This structure was considerably reduced with non-polymerizing laminin, fully blocked by E3, and unaffected by Ha2/5. Although it formed in the absence of type IV collagen, it was nonetheless able to incorporate this collagen. Finally, cell competency to bind laminin and form a basement membrane was passage-dependent. We postulate that laminin induces the assembly of a basement membrane on competent cell surfaces probably mediated by anchorage through LG 4-5. Upon binding, laminin interacts with dystroglycan, mobilizes utrophin, and assembles a 'nascent' basement membrane, independent of integrin, that is completed by incorporation of type IV collagen. However, the fibrillar beta1-integrin dependent matrix is unlikely to be precursor to basement membrane.