Plasma Proteome-Based Test for First-Line Treatment Selection in Metastatic Non-Small Cell Lung Cancer.

PURPOSE: Current guidelines for the management of metastatic non-small cell lung cancer (NSCLC) without driver mutations recommend checkpoint immunotherapy with PD-1/PD-L1 inhibitors, either alone or in combination with chemotherapy. This approach fails to account for individual patient variability and host immune factors and often results in less-than-ideal outcomes. To address the limitations of the current guidelines, we developed and subsequently blindly validated a machine learning algorithm using pretreatment plasma proteomic profiles for personalized treatment decisions. PATIENTS AND METHODS: We conducted a multicenter observational trial (ClinicalTrials.gov identifier: NCT04056247) of patients undergoing PD-1/PD-L1 inhibitor-based therapy (n = 540) and an additional patient cohort receiving chemotherapy (n = 85) who consented to pretreatment plasma and clinical data collection. Plasma proteome profiling was performed using SomaScan Assay v4.1. RESULTS: Our test demonstrates a strong association between model output and clinical benefit (CB) from PD-1/PD-L1 inhibitor-based treatments, evidenced by high concordance between predicted and observed CB (R2 = 0.98, P < .001). The test categorizes patients as either PROphet-positive or PROphet-negative and further stratifies patient outcomes beyond PD-L1 expression levels. The test successfully differentiates between PROphet-negative patients exhibiting high tumor PD-L1 levels (≥50%) who have enhanced overall survival when treated with a combination of immunotherapy and chemotherapy compared with immunotherapy alone (hazard ratio [HR], 0.23 [95% CI, 0.1 to 0.51], P = .0003). By contrast, PROphet-positive patients show comparable outcomes when treated with immunotherapy alone or in combination with chemotherapy (HR, 0.78 [95% CI, 0.42 to 1.44], P = .424). CONCLUSION: Plasma proteome-based testing of individual patients, in combination with standard PD-L1 testing, distinguishes patient subsets with distinct differences in outcomes from PD-1/PD-L1 inhibitor-based therapies. These data suggest that this approach can improve the precision of first-line treatment for metastatic NSCLC.

Biological insights from plasma proteomics of non-small cell lung cancer patients treated with immunotherapy.

Introduction: Immune checkpoint inhibitors have made a paradigm shift in the treatment of non-small cell lung cancer (NSCLC). However, clinical response varies widely and robust predictive biomarkers for patient stratification are lacking. Here, we characterize early on-treatment proteomic changes in blood plasma to gain a better understanding of treatment response and resistance. Methods: Pre-treatment (T0) and on-treatment (T1) plasma samples were collected from 225 NSCLC patients receiving PD-1/PD-L1 inhibitor-based regimens. Plasma was profiled using aptamer-based technology to quantify approximately 7000 plasma proteins per sample. Proteins displaying significant fold changes (T1:T0) were analyzed further to identify associations with clinical outcomes using clinical benefit and overall survival as endpoints. Bioinformatic analyses of upregulated proteins were performed to determine potential cell origins and enriched biological processes. Results: The levels of 142 proteins were significantly increased in the plasma of NSCLC patients following ICI-based treatments. Soluble PD-1 exhibited the highest increase, with a positive correlation to tumor PD-L1 status, and, in the ICI monotherapy dataset, an association with improved overall survival. Bioinformatic analysis of the ICI monotherapy dataset revealed a set of 30 upregulated proteins that formed a single, highly interconnected network, including CD8A connected to ten other proteins, suggestive of T cell activation during ICI treatment. Notably, the T cell-related network was detected regardless of clinical benefit. Lastly, circulating proteins of alveolar origin were identified as potential biomarkers of limited clinical benefit, possibly due to a link with cellular stress and lung damage. Conclusions: Our study provides insights into the biological processes activated during ICI-based therapy, highlighting the potential of plasma proteomics to identify mechanisms of therapy resistance and biomarkers for outcome.

PEDF-derived peptide protects against Amyloid-ß toxicity in vitro and prevents retinal dysfunction in rats.

Amyloid-beta (Aß), a family of aggregation-prone and neurotoxic peptides, has been implicated in the pathophysiology of age-related macular degeneration (AMD). We have previously shown that oligomeric and fibrillar species of Aß42 exerted retinal toxicity in rats, but while the consequences of exposure to amyloid were related to intracellular effects, the mechanism of Aß42 internalization in the retina is not well characterized. In the brain, the 67 kDa laminin receptor (67LR) participates in Aß-related neuronal cell death. A short peptide derived from pigment epithelium-derived factor (PEDF), formerly designated PEDF-335, was found to mitigate experimental models of ischemic retinopathy via targeting of 67LR. In the present study, we hypothesized that 67LR mediates the uptake of pathogenic Aß42 assemblies in the retina, and that targeting of this receptor by PEDF-335 may limit the internalization of Aß, thereby ameliorating its retinotoxicity. To test this assumption ARPE-19 cells in culture were incubated with PEDF-335 before treatment with fibrillar or oligomeric structures of Aß42. Immunostaining confirmed that PEDF-335 treatment substantially prevented amyloid internalization into ARPE-19 cells and maintained their viability in the presence of toxic oligomeric and fibrillar Aß42 entities in vitro. FRET competition assay was performed and confirmed the binding of PEDF-335 to 67LR in RPE-like cells. Wild-type rats were treated with intravitreal PEDF-335 in the experimental eye 2 days prior to administration of retinotoxic Aß42 oligomers or fibrils to both eyes. Retinal function was assessed by electroretinography through 6 weeks post injection. The ERG responses in rats treated with oligomeric or fibrillar Aß42 assemblies were near-normal in eyes previously treated with intravitreal PEDF-335, whereas those measured in the control eyes treated with injection of the Aß42 assemblies alone showed pathologic attenuation of the retinal function through 6 weeks. The retinal presence of 67LR was determined ex vivo by immunostaining and western blotting. Retinal staining demonstrated the constitutional expression of 67LR mainly in the retinal nuclear layers. In the presence of Aß42, the levels of 67LR were increased, although its retinal distribution remained largely unaltered. In contrast, no apparent differences in the retinal expression level of 67LR were noted following exposure to PEDF-335 alone, and its pattern of localization in the retina remained similarly concentrated primarily in the inner and outer nuclear layers. In summary, we found that PEDF-335 confers protection against Aß42-mediated retinal toxicity, with significant effects noted in cells as well as in vivo in rats. The effects of PEDF-335 in the retina are potentially mediated via binding to 67LR and by at least partial inhibition of Aß42 internalization. These results suggest that PEDF-335 may merit further consideration in the development of targeted inhibition of amyloid-related toxicity in the retina. More broadly, our observations provide evidence on the importance of extracellular versus intracellular Aß42 in the retina and suggest concepts on the molecular mechanism of Aß retinal pathogenicity.

The Surprising Nonlinear Effects of S100A9 Proteins in the Retina.

Age-related macular degeneration (AMD) is a complex disease in which inflammation is implicated as a key factor but the precise molecular mechanisms are poorly understood. AMD lesions contain an excess of the pro-inflammatory S100A9 protein, but its retinal significance was yet unexplored. S100A9 was shown to be intrinsically amyloidogenic in vitro and in vivo. Here, we hypothesized that the retinal effects of S100A9 are related to its supramolecular conformation. ARPE-19 cultures were treated with native dimeric and fibrillar S100A9 preparations, and cell viability was determined. Wild-type rats were treated intravitreally with the S100A9 solutions in the right eye and with the vehicle in the left. Retinal function was assessed longitudinally by electroretinography (ERG), comparing the amplitudes and configurations for each intervention. Native S100A9 had no impact on cellular viability in vitro or on the retinal function in vivo. Despite dispersed intracellular uptake, fibrillar S100A9 did not decrease ARPE-19 cell viability. In contrast, S100A9 fibrils impaired retinal function in vivo following intravitreal injection in rats. Intriguingly, low-dose fibrillar S100A9 induced contrasting in vivo effects, significantly increasing the ERG responses, particularly over 14 days postinjection. The retinal effects of S100A9 were further characterized by glial and microglial cell activation. We provide the first indication for the retinal effects of S100A9, showing that its fibrils inflicted retinal dysfunction and glial activation in vivo, while low dose of the same assemblies resulted in an unpredicted enhancement of the ERG amplitudes. These nonlinear responses highlight the consequences of self-assembly of S100A9 and provide insight into its pathophysiological and possibly physiological roles in the retina.

Perceptual stability reflected in neuronal pattern similarities in human visual cortex.

The magnitude of neuronal activation is commonly considered a critical factor for conscious perception of visual content. However, this dogma contrasts with the phenomenon of rapid adaptation, in which the magnitude of neuronal activation drops dramatically in a rapid manner while the visual stimulus and the conscious experience it elicits remain stable. Here, we report that the profiles of multi-site activation patterns and their relational geometry-i.e., the similarity distances between activation patterns, as revealed using intracranial electroencephalographic (iEEG) recordings-are sustained during extended visual stimulation despite the major magnitude decrease. These results are compatible with the hypothesis that conscious perceptual content is associated with the neuronal pattern profiles and their similarity distances, rather than the overall activation magnitude, in human visual cortex.

Longitudinal plasma proteomic profiling of patients with non-small cell lung cancer undergoing immune checkpoint blockade.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have revolutionized the cancer therapy landscape due to long-term benefits in patients with advanced metastatic disease. However, robust predictive biomarkers for response are still lacking and treatment resistance is not fully understood. METHODS: We profiled approximately 800 pre-treatment and on-treatment plasma proteins from 143 ICI-treated patients with non-small cell lung cancer (NSCLC) using ELISA-based arrays. Different clinical parameters were collected from the patients including specific mutations, smoking habits, and body mass index, among others. Machine learning algorithms were used to identify a predictive signature for response. Bioinformatics tools were used for the identification of patient subtypes and analysis of differentially expressed proteins and pathways in each response group. RESULTS: We identified a predictive signature for response to treatment comprizing two proteins (CXCL8 and CXCL10) and two clinical parameters (age and sex). Bioinformatic analysis of the proteomic profiles identified three distinct patient clusters that correlated with multiple parameters such as response, sex and TNM (tumors, nodes, and metastasis) staging. Patients who did not benefit from ICI therapy exhibited significantly higher plasma levels of several proteins on-treatment, and enrichment in neutrophil-related proteins. CONCLUSIONS: Our study reveals potential biomarkers in blood plasma for predicting response to ICI therapy in patients with NSCLC and sheds light on mechanisms underlying therapy resistance.

Disrupted neural correlates of anesthesia and sleep reveal early circuit dysfunctions in Alzheimer models.

Dysregulated homeostasis of neural activity has been hypothesized to drive Alzheimer's disease (AD) pathogenesis. AD begins with a decades-long presymptomatic phase, but whether homeostatic mechanisms already begin failing during this silent phase is unknown. We show that before the onset of memory decline and sleep disturbances, familial AD (fAD) model mice display no deficits in CA1 mean firing rate (MFR) during active wakefulness. However, homeostatic down-regulation of CA1 MFR is disrupted during non-rapid eye movement (NREM) sleep and general anesthesia in fAD mouse models. The resultant hyperexcitability is attenuated by the mitochondrial dihydroorotate dehydrogenase (DHODH) enzyme inhibitor, which tunes MFR toward lower set-point values. Ex vivo fAD mutations impair downward MFR homeostasis, resulting in pathological MFR set points in response to anesthetic drug and inhibition blockade. Thus, firing rate dyshomeostasis of hippocampal circuits is masked during active wakefulness but surfaces during low-arousal brain states, representing an early failure of the silent disease stage.

Host response to immune checkpoint inhibitors contributes to tumor aggressiveness.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have made a paradigm shift in clinical oncology due to unprecedented long-term remissions. However, only a small proportion of patients respond to ICI therapy. It is, therefore, essential to understand the mechanisms driving therapy resistance and to develop strategies for increasing response rates. We previously demonstrated that in response to various cancer treatment modalities, the host activates a range of biological processes that promote tumor regrowth and metastasis. Here, we characterize the host-mediated response to ICI therapy, and investigate its contribution to therapy resistance. METHODS: Tumor cell migration, invasion and motility were assessed in the presence of plasma from ICI-treated mice and patients. Immune cell composition in peripheral blood and tumors of ICI-treated mice was assessed by flow and mass cytometry. Plasma host factors driving tumor aggressiveness were identified by proteomic profiling, followed by bioinformatic analysis. The therapeutic effect of inhibiting host-mediated processes in ICI-treated mice was assessed in a tumor model. RESULTS: Tumor cells exhibit enhanced migratory and invasive properties in vitro on exposure to plasma from anti-PD1-treated mice. Moreover, mice intravenously injected with plasma-exposed tumor cells display increased metastatic burden and mortality rate in comparison to control arms. Furthermore, tumors from anti-PD1-treated mice as well as Matrigel plugs containing plasma from anti-PD1-treated mice are highly infiltrated with immune cell types associated with both antitumor and protumor activity. These collective findings suggest that anti-PD1 treatment induces a systemic host response that potentially counteracts the drug's therapeutic activity. Proteomic profiling of plasma from anti-PD1-treated mice reveals an activation of multiple biological pathways associated with tumor aggressiveness. Consequently, blocking IL-6, one of the key drivers of the identified biological pathways, counteracts ICI-induced metastatic properties in vitro and improves ICI treatment efficacy in vivo. Lastly, plasma samples from ICI-treated non-small cell lung cancer patients differentially affect tumor cell aggressiveness in vitro, with enhanced tumor cell motility correlating with a worse clinical outcome. CONCLUSIONS: ICI therapy induces host-mediated processes that contribute to therapy resistance. Identification and analysis of such processes may lead to the discovery of biomarkers for clinical response and strategies for overcoming therapy resistance.

Serine Biosynthesis Is a Metabolic Vulnerability in IDH2-Driven Breast Cancer Progression.

Cancer-specific metabolic phenotypes and their vulnerabilities represent a viable area of cancer research. In this study, we explored the association of breast cancer subtypes with different metabolic phenotypes and identified isocitrate dehydrogenase 2 (IDH2) as a key player in triple-negative breast cancer (TNBC) and HER2. Functional assays combined with mass spectrometry-based analyses revealed the oncogenic role of IDH2 in cell proliferation, anchorage-independent growth, glycolysis, mitochondrial respiration, and antioxidant defense. Genome-scale metabolic modeling identified phosphoglycerate dehydrogenase (PHGDH) and phosphoserine aminotransferase (PSAT1) as the synthetic dosage lethal (SDL) partners of IDH2. In agreement, CRISPR-Cas9 knockout of PHGDH and PSAT1 showed the essentiality of serine biosynthesis proteins in IDH2-high cells. The clinical significance of the SDL interaction was supported by patients with IDH2-high/PHGDH-low tumors, who exhibited longer survival than patients with IDH2-high/PHGDH-high tumors. Furthermore, PHGDH inhibitors were effective in treating IDH2-high cells in vitro and in vivo. Altogether, our study creates a new link between two known cancer regulators and emphasizes PHGDH as a promising target for TNBC with IDH2 overexpression. SIGNIFICANCE: These findings highlight the metabolic dependence of IDH2 on the serine biosynthesis pathway, adding an important layer to the connection between TCA cycle and glycolysis, which can be translated into novel targeted therapies.

Clinical Proteomics of Metastatic Melanoma Reveals Profiles of Organ Specificity and Treatment Resistance.

PURPOSE: Treatment of metastatic melanoma has dramatically improved in recent years, thanks to the development of immunotherapy and BRAF-MEK-targeted therapies. However, these developments revealed marked heterogeneity in patient response, which is yet to be fully understood. In this work, we aimed to associate the proteomic profiles of metastatic melanoma with the patient clinical information, to identify protein correlates with metastatic location and prior treatments. EXPERIMENTAL DESIGN: We performed mass spectrometry-based proteomic analysis of 185 metastatic melanoma samples and followed with bioinformatics analysis to examine the association of metastatic location, BRAF status, survival, and immunotherapy response with the tumor molecular profiles. RESULTS: Bioinformatics analysis showed a high degree of functional heterogeneity associated with the site of metastasis. Lung metastases presented higher immune-related proteins, and higher mitochondrial-related processes, which were shown previously to be associated with better immunotherapy response. In agreement, epidemiological analysis of data from the National Cancer Database showed improved response to anti-programmed death 1, mainly in patients with lung metastasis. Focus on lung metastases revealed prognostic and molecular heterogeneity and highlighted potential tissue-specific biomarkers. Analysis of the BRAF mutation status and prior treatments with MAPK inhibitors proposed the molecular basis of the effect on immunotherapy response and suggested coordinated combination of immunotherapy and targeted therapy may increase treatment efficacy. CONCLUSIONS: Altogether, the proteomic data provided novel molecular determinants of critical clinical features, including the effects of sequential treatments and metastatic locations. These results can be the basis for development of site-specific treatments toward treatment personalization.

Phosphoproteomics reveals novel modes of function and inter-relationships among PIKKs in response to genotoxic stress.

The DNA damage response (DDR) is a complex signaling network that relies on cascades of protein phosphorylation, which are initiated by three protein kinases of the family of PI3-kinase-related protein kinases (PIKKs): ATM, ATR, and DNA-PK. ATM is missing or inactivated in the genome instability syndrome, ataxia-telangiectasia (A-T). The relative shares of these PIKKs in the response to genotoxic stress and the functional relationships among them are central questions in the genome stability field. We conducted a comprehensive phosphoproteomic analysis in human wild-type and A-T cells treated with the double-strand break-inducing chemical, neocarzinostatin, and validated the results with the targeted proteomic technique, selected reaction monitoring. We also matched our results with 34 published screens for DDR factors, creating a valuable resource for identifying strong candidates for novel DDR players. We uncovered fine-tuned dynamics between the PIKKs following genotoxic stress, such as DNA-PK-dependent attenuation of ATM. In A-T cells, partial compensation for ATM absence was provided by ATR and DNA-PK, with distinct roles and kinetics. The results highlight intricate relationships between these PIKKs in the DDR.

Breast Cancer-Derived Microparticles Reduce Cancer Cell Adhesion, an Effect Augmented by Chemotherapy.

Tumor cell heterogeneity is primarily dictated by mutational changes, sometimes leading to clones that undergo a metastatic switch. However, little is known about tumor heterogeneity following chemotherapy perturbation. Here we studied the possible involvement of tumor-derived extracellular vesicles, often referred to as tumor-derived microparticles (TMPs), as mediators of the metastatic switch in the tumor microenvironment by hindering cell adhesion properties. Specifically, we show that highly metastatic or chemotherapy-treated breast cancer cells shed an increased number of TMPs compared to their respective controls. We found that these TMPs substantially reduce cell adhesion and disrupt actin filament structure, therefore increasing their biomechanical force pace, further implicating tumor cell dissemination as part of the metastatic cascade. Our results demonstrate that these pro-metastatic effects are mediated in part by CD44 which is highly expressed in TMPs obtained from highly metastatic cells or cells exposed to chemotherapy when compared to cells with low metastatic potential. Consequently, when we inhibited CD44 expression on TMPs by a pharmacological or a genetic approach, increased tumor cell adhesion and re-organized actin filament structure were observed. We also demonstrated that breast cancer patients treated with paclitaxel chemotherapy exhibited increased CD44-expressing TMPs. Overall, our study provides further insights into the role of TMPs in promoting metastasis, an effect which is augmented when tumor cells are exposed to chemotherapy.

PDZD8 interacts with Protrudin and Rab7 at ER-late endosome membrane contact sites associated with mitochondria.

Endosomes are compositionally dynamic organelles that regulate signaling, nutrient status and organelle quality by specifying whether material entering the cells will be shuttled back to the cell surface or degraded by the lysosome. Recently, membrane contact sites (MCSs) between the endoplasmic reticulum (ER) and endosomes have emerged as important players in endosomal protein sorting, dynamics and motility. Here, we show that PDZD8, a Synaptotagmin-like Mitochondrial lipid-binding Proteins (SMP) domain-containing ER transmembrane protein, utilizes distinct domains to interact with Rab7-GTP and the ER transmembrane protein Protrudin and together these components localize to an ER-late endosome MCS. At these ER-late endosome MCSs, mitochondria are also recruited to form a three-way contact. Thus, our data indicate that PDZD8 is a shared component of two distinct MCSs and suggest a role for SMP-mediated lipid transport in the regulation of endosome function.

Inter-participant consistency of language-processing networks during abstract thoughts.

Human brain imaging typically employs structured and controlled tasks to avoid variable and inconsistent activation patterns. Here we expand this assumption by showing that an extremely open-ended, high-level cognitive task of thinking about an abstract content, loosely defined as "abstract thinking" - leads to highly consistent activation maps. Specifically, we show that activation maps generated during such cognitive process were precisely located relative to borders of well-known networks such as internal speech, visual and motor imagery. The activation patterns allowed decoding the thought condition at >95%. Surprisingly, the activated networks remained the same regardless of changes in thought content. Finally, we found remarkably consistent activation maps across individuals engaged in abstract thinking. This activation bordered, but strictly avoided visual and motor networks. On the other hand, it overlapped with left lateralized language networks. Activation of the default mode network (DMN) during abstract thought was similar to DMN activation during rest. These observations were supported by a quantitative neuronal distance metric analysis. Our results reveal that despite its high level, and varied content nature - abstract thinking activates surprisingly precise and consistent networks in participants' brains.

The Noisy Brain: Power of Resting-State Fluctuations Predicts Individual Recognition Performance.

The unique profile of strong and weak cognitive traits characterizing each individual is of a fundamental significance, yet their neurophysiological underpinnings remain elusive. Here, we present intracranial electroencephalogram (iEEG) measurements in humans pointing to resting-state cortical "noise" as a possible neurophysiological trait that limits visual recognition capacity. We show that amplitudes of slow (<1 Hz) spontaneous fluctuations in high-frequency power measured during rest were predictive of the patients' performance in a visual recognition 1-back task (26 patients, total of 1,389 bipolar contacts pairs). Importantly, the effect was selective only to task-related cortical sites. The prediction was significant even across long (mean distance 4.6 ± 2.8 days) lags. These findings highlight the level of the individuals' internal "noise" as a trait that limits performance in externally oriented demanding tasks.

Convergent evolution of face spaces across human face-selective neuronal groups and deep convolutional networks.

The discovery that deep convolutional neural networks (DCNNs) achieve human performance in realistic tasks offers fresh opportunities for linking neuronal tuning properties to such tasks. Here we show that the face-space geometry, revealed through pair-wise activation similarities of face-selective neuronal groups recorded intracranially in 33 patients, significantly matches that of a DCNN having human-level face recognition capabilities. This convergent evolution of pattern similarities across biological and artificial networks highlights the significance of face-space geometry in face perception. Furthermore, the nature of the neuronal to DCNN match suggests a role of human face areas in pictorial aspects of face perception. First, the match was confined to intermediate DCNN layers. Second, presenting identity-preserving image manipulations to the DCNN abolished its correlation to neuronal responses. Finally, DCNN units matching human neuronal group tuning displayed view-point selective receptive fields. Our results demonstrate the importance of face-space geometry in the pictorial aspects of human face perception.

The landscape of tiered regulation of breast cancer cell metabolism.

Altered metabolism is a hallmark of cancer, but little is still known about its regulation. In this study, we measure transcriptomic, proteomic, phospho-proteomic and fluxomics data in a breast cancer cell-line (MCF7) across three different growth conditions. Integrating these multiomics data within a genome scale human metabolic model in combination with machine learning, we systematically chart the different layers of metabolic regulation in breast cancer cells, predicting which enzymes and pathways are regulated at which level. We distinguish between two types of reactions, directly and indirectly regulated. Directly-regulated reactions include those whose flux is regulated by transcriptomic alterations (~890) or via proteomic or phospho-proteomics alterations (~140) in the enzymes catalyzing them. We term the reactions that currently lack evidence for direct regulation as (putative) indirectly regulated (~930). Many metabolic pathways are predicted to be regulated at different levels, and those may change at different media conditions. Remarkably, we find that the flux of predicted indirectly regulated reactions is strongly coupled to the flux of the predicted directly regulated ones, uncovering a tiered hierarchical organization of breast cancer cell metabolism. Furthermore, the predicted indirectly regulated reactions are predominantly reversible. Taken together, this architecture may facilitate rapid and efficient metabolic reprogramming in response to the varying environmental conditions incurred by the tumor cells. The approach presented lays a conceptual and computational basis for mapping metabolic regulation in additional cancers.

Proteomics of Melanoma Response to Immunotherapy Reveals Mitochondrial Dependence.

Immunotherapy has revolutionized cancer treatment, yet most patients do not respond. Here, we investigated mechanisms of response by profiling the proteome of clinical samples from advanced stage melanoma patients undergoing either tumor infiltrating lymphocyte (TIL)-based or anti- programmed death 1 (PD1) immunotherapy. Using high-resolution mass spectrometry, we quantified over 10,300 proteins in total and ∼4,500 proteins across most samples in each dataset. Statistical analyses revealed higher oxidative phosphorylation and lipid metabolism in responders than in non-responders in both treatments. To elucidate the effects of the metabolic state on the immune response, we examined melanoma cells upon metabolic perturbations or CRISPR-Cas9 knockouts. These experiments indicated lipid metabolism as a regulatory mechanism that increases melanoma immunogenicity by elevating antigen presentation, thereby increasing sensitivity to T cell mediated killing both in vitro and in vivo. Altogether, our proteomic analyses revealed association between the melanoma metabolic state and the response to immunotherapy, which can be the basis for future improvement of therapeutic response.

Hippocampal sharp-wave ripples linked to visual episodic recollection in humans.

Hippocampal sharp-wave ripples (SWRs) constitute one of the most synchronized activation events in the brain and play a critical role in offline memory consolidation. Yet their cognitive content and function during awake, conscious behavior remains unclear. We directly examined this question using intracranial recordings in human patients engaged in episodic free recall of previously viewed photographs. Our results reveal a content-selective increase in hippocampal ripple rate emerging 1 to 2 seconds prior to recall events. During recollection, high-order visual areas showed pronounced SWR-coupled reemergence of activation patterns associated with recalled content. Finally, the SWR rate during encoding predicted subsequent free-recall performance. These results point to a role for hippocampal SWRs in triggering spontaneous recollections and orchestrating the reinstatement of cortical representations during free episodic memory retrieval.