Analytical validation of the PROphet test for treatment decision-making guidance in metastatic non-small cell lung cancer

The blood proteome, consisting of thousands of proteins engaged in various biological processes, acts as a valuable source of potential biomarkers for various medical applications. PROphet is a plasma proteomics-based test that serves as a decision-support tool for non-small cell lung cancer (NSCLC) patients, combining proteomic profiling using SomaScan technology and subsequent computational algorithm. PROphet was implemented as a laboratory developed test (LDT). Under the Clinical Laboratory Improvement Amendments (CLIA) and Commission on Office Laboratory Accreditation (COLA) regulations, prior to releasing patient test results, a clinical laboratory located in the United States employing an LDT must examine its performance characteristics with regard to analytical validity. This study describes the experimental and computational analytical validity of the PROphet test, as required by CLIA/COLA regulations. Experimental precision analysis displayed a median coefficient of variation (CV) of 3.9 % and 4.7 % for intra-plate and inter-plate examination, respectively, and the median accuracy rate between sites was 88 %. Computational precision exhibited a high accuracy rate, with 93 % of samples displaying complete concordance in results. A cross-platform comparison between SomaScan and other proteomics platforms yielded a median Spearman's rank correlation coefficient of 0.51, affirming the consistency and reliability of the SomaScan platform as used under the PROphet test. Our study presents a robust framework for evaluating the analytical validity of a platform that combines an experimental assay with subsequent computational algorithms. When applied to the PROphet test, strong analytical performance of the test was demonstrated.

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.

300 Longitudinal plasma proteomic profiling of non-small cell lung cancer patients undergoing immune checkpoint blockade-based therapy

Background

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment by shifting the focus from the tumor to the immune system of the host. Despite durable response to ICIs, only a small proportion of non-small lung cancer (NSCLC) patients respond to this treatment. Thus, great effort is currently focused on uncovering mechanisms of resistance and identifying predictive biomarkers for outcome.

Methods

Blood plasma was obtained from 143 NSCLC patients treated with ICI-based therapy at baseline and early on-treatment (following the first treatment), and the levels of approximately 800 proteins were determined using ELISA-based arrays. Bioinformatic analysis was performed in order to detect novel patterns of resistance to ICI-based therapy. To identify a signature that predicts clinical outcome, a machine learning algorithm was applied.

Results

Unsupervised bioinformatic analysis of the plasma proteomic profiles classified the patients into 3 clusters with distinct clinical and biological features. Patients in cluster #1 exhibited resistance to therapy, bone metastasis and high TNM (tumors, nodes and metastasis) staging; this cluster displayed high levels of proteins related to glycan and pyrimidine metabolism and cell-adhesion. Cluster #2 was enriched with responders, males, and patients with low TNM staging; this cluster displayed a strong representation of desmoglein proteins. Cluster #3 was enriched with female patients while the proteome of these patients displayed high levels of MAPK signaling related proteins. Patient clusters were largely unchanged when comparing baseline and on-treatment data, suggesting pre-existing rather than acquired resistance to therapy. A further comparison between responders and non-responders identified six significantly differentially expressed proteins comprised of both host- and tumor-related proteins, with non-responders displaying a significant enrichment of neutrophil proteins at baseline and early-on-treatment. Notably, there was no significant difference in the neutrophil count between responders and non-responders, suggesting a functional shift in neutrophils upon treatment in non-responders. Lastly, we identified a predictive signature for response comprised of two proteins and two clinical features. The performance of the predictive signature reached an area under the curve (AUC) of the receiver operating characteristics (ROC) plot of 0.8 in an independent validation subset of the cohort, indicating a high predictive power.

Conclusions

Here we performed a deep bioinformatic analysis of plasma proteome profiles of 143 NSCLC patients undergoing ICI-based therapy. Our study sheds light on underlying mechanisms of resistance to ICI-based therapy and reveals a predictive signature for response in NSCLC patients.

Ethics Approval

Data and study specimens were purchased from Indivumed and Sheba medical center, approval number 0226-13-SMC (institutional review board). Participants gave informed consent before taking part.

Integration of proteomic and clinical data for the prediction of response to immune checkpoint inhibitor therapy in non-small cell lung cancer

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Background: Immune checkpoint inhibitor (ICI) therapy represents one of the most promising cancer treatments to date. However, despite unprecedented rates of durable response, only a small proportion of patients benefits from this approach. Major efforts are therefore required to characterize treatment resistance mechanisms, as well as to identify reliable biomarkers for response. We have previously shown that in response to various types of cancer therapy, including ICIs, the host may induce pro-tumorigenic processes that can promote therapy resistance. Here we examined systemic host-response proteomic profiles in non-small cell lung cancer (NSCLC) patients, aiming to discover biomarkers for response to ICI therapy and to unravel underlying resistance mechanisms. Methods: As part of our ongoing PROPHETIC clinical trial (NCT04056247), plasma samples were obtained at baseline (T0) and early-on treatment (T1; following the first treatment) from 120 NSCLC patients receiving ICI therapy. Proteomic profiling of the plasma samples was performed using proximity-extension assay (PEA) technology; validation was carried out for a fraction of the samples using ELISA-based arrays. To identify a proteomic signature that predicts clinical outcome, machine learning algorithms were applied following a random separation of the cohort into a discovery set and a validation set. Results: A proteomic signature predictive of response to treatment was identified and validated. Bioinformatic analysis identified potential mechanisms of resistance based on differentially expressed proteins associated with pro-tumorigenic biological processes. Statistical analysis of the clinical data identified multiple novel differential clinical parameters between responders and non-responders, either at baseline or by comparing T0 to T1, which may suggest host-mediated effects. Conclusions: Our study demonstrates the potential clinical utility of analyzing the host response to ICI therapy, in particular for the discovery of novel predictive biomarkers for NSCLC patient stratification. Clinical trial information: NCT04056247.

The neuropsychological profile of patients with 3-methylglutaconic aciduria type III, Costeff syndrome

Costeff syndrome is a rare genetic neuro-ophthalmological syndrome consisting of early-onset bilateral optic atrophy along with a progressive complex motor disorder with elevated levels of urinary 3-methylglutaconic acid and 3-methylglutaric acid. While borderline to mild cognitive deficits have been considered to be common in patients with this syndrome, a comprehensive cognitive assessment has never been performed. The aim of the current study was to explore the cognitive profile associated with Costeff syndrome. Sixteen adult patients diagnosed with Costeff syndrome were administered a neuropsychological test battery that was composed of standardized verbal tests adapted for the blind. General intelligence ranged from average to borderline, with a group mean consistent with intact general cognitive functioning (VIQmean  = 85, z = -1) in the low-average range of the general population. The auditory immediate and delayed memory indexes were in the average range and were significantly higher than the general cognitive functioning, whereas the working memory index was significantly lower than the general cognitive functioning. Adult patients with Costeff syndrome have intact global cognition and learning abilities and strong auditory memory performance. © 2015 Wiley Periodicals, Inc.

An Antibody-based Blood Test Utilizing a Panel of Biomarkers as a New Method for Improved Breast Cancer Diagnosis

In order to develop a new tool for diagnosis of breast cancer based on autoantibodies against a panel of biomarkers, a clinical trial including blood samples from 507 subjects was conducted. All subjects showed a breast abnormality on exam or breast imaging and final biopsy pathology of either breast cancer patients or healthy controls. Using an enzyme-linked immunosorbent assay, the samples were tested for autoantibodies against a predetermined number of biomarkers in various models that were used to determine a diagnosis, which was compared to the clinical status. Our new assay achieved a sensitivity of 95.2% [CI = 92.8–96.8%] at a fixed specificity of 49.5%. Receiver-operator characteristic curve analysis showed an area under the curve of 80.1% [CI = 72.6–87.6%]. These results suggest that a blood test which is based on models comprising several autoantibodies to specific biomarkers may be a new and novel tool for improving the diagnostic evaluation of breast cancer.

Familial Mediterranean fever (FMF) and multiple sclerosis: an association study in one of the world's largest FMF cohorts

BACKGROUND AND PURPOSE

  To describe and characterize the association between familial Mediterranean fever (FMF) and multiple sclerosis (MS).

METHODS

  The patient registry of The National Center for FMF was screened for the coexistence of FMF and MS. Tel-Hashomer criteria were used for the diagnosis of FMF, and FMF severity was evaluated, using the simplified FMF severity scale. McDonald criteria were used for the diagnosis of MS, and neurologic disability was measured using the expanded disability status scale (EDSS).

RESULTS

  We identified nine patients, affected with both FMF and MS. The onset of the FMF averaged 15.6 (3-37) years. Most patients suffered from abdominal and joint attacks, and 50% of the patients sustained a moderate to severe FMF. The onset of the MS was at an average age of 31.6 (17-50) years. Neurologic manifestations varied individually, without a dominant deficit, and the course was in a relapsing-remitting pattern in most. The median EDSS was in general of low score (3.0), apart from the patients who were homozygous for the M694V mutation, in whom the MS was more severe. Based on our case series, the frequency of MS in our FMF population is 0.075%, twice higher the expected rate in the general population (P=0.0057).

CONCLUSIONS

  Multiple sclerosis is more common in FMF than in the general Israeli population. Homozygosity for the M694V MEFV mutation may aggravate the phenotype of MS and predispose FMF patients to develop MS.

Internal obturator muscle abscess caused by Klebsiella pneumoniae

Obturator internus muscle abscess is an infrequent form of pyomyositis. To date, this disease has been described almost exclusively in children and young adults, and in most cases the causative agents are Gram-positive bacteria. We present the first report of obturator internus muscle abscess caused by a highly antibiotic resistant Klebsiella pneumoniae, in an elderly diabetic patient. Once considered very rare, Gram-negative pyomyositis is increasingly reported, and is an important concern in diabetic patients. Since pyomyositis can easily be missed if not considered, physicians should become familiar with this condition, and consider it in the differential diagnosis of septic diabetic patients.

AUG sequences are required to sustain nonsense-codon-mediated suppression of splicing

More than 90% of human genes are rich in intronic latent 5' splice sites whose utilization in pre-mRNA splicing would introduce in-frame stop codons into the resultant mRNAs. We have therefore hypothesized that suppression of splicing (SOS) at latent 5' splice sites regulates alternative 5' splice site selection in a way that prevents the production of toxic nonsense mRNAs and verified this idea by showing that the removal of such in-frame stop codons is sufficient to activate latent splicing. Splicing control by SOS requires recognition of the mRNA reading frame, presumably recognizing the start codon sequence. Here we show that AUG sequences are indeed essential for SOS. Although protein translation does not seem to be required for SOS, the first AUG is shown here to be necessary but not sufficient. We further show that latent splicing can be elicited upon treatment with pactamycin-a drug known to block translation by its ability to recognize an RNA fold-but not by treatment with other drugs that inhibit translation through other mechanisms. The effect of pactamycin on SOS is dependent neither on steady-state translation nor on the pioneer round of translation. This effect is found for both transfected and endogenous genes, indicating that SOS is a natural mechanism.

Hand rhythmic tapping and timing in Parkinson's disease

BACKGROUND

Dysrhythmia is one of the features frequently associated with the motor disturbance in Parkinson's disease (PD). The mechanism responsible for this phenomenon is not known.

OBJECTIVES

To assess the rhythmic movements of the hand in PD patients in general and in parkinsonian subtypes.

METHODS

Fifty-one PD patients (32 males) with mean age 66.3 +/- 9.1 years (6.6 years of symptoms) and 36 healthy controls (age 64.9 +/- 13.2, range 40-85) were studied. Subjects were asked to tap with their dominant or less affected arm on a digitized switch board at their most comfortable pace (16 s), fastest tapping speed (12 s), and at different frequencies provided by a metronome. The mean rhythm and the tap-to-tap variation were compared. Performance of the PD patients and control subjects were compared, as there were different subtypes of PD patients. Patients were subclassified into: tremor predominant (TP) (14 patients), freezing predominant (FP) (11 patients), akinetic-rigid (AR) (12 patients) and an unclassified group (UC) (14 patients). Results. There was no significance difference between patients and controls in the self-chosen, most comfortable tapping rate or in the tap-to-tap variation of the self-paced task. PD patients tapped at a significantly slower rate than controls when asked to tap at their fastest rate (4.39 +/- 1.32 vs. 5.14 +/- 1.31 Hz; p < 0.01). This difference was the result of an especially slow performance of the TP and AR subgroups (3.85+/-1.20 and 3.88+/-1.46, respectively; p < 0.01 compared to the control group). TP was the only subgroup to show an increased tap-to-tap variation at their fastest tapping rate compared to the control group (0.070 +/- 0.057 vs. 0.029 +/- 0.025 s, respectively, p < 0.05). The TP subgroup also showed hastening when they followed an externally given rhythm of 2.5 Hz and they tapped at 2.73 +/- 0.36 Hz p < 0.05).

CONCLUSIONS

Externally driven and self-paced tapping are preserved in patients with PD, when examined at their best 'on' state. The tremor predominant subgroup seems to have specific pacing disturbances.

Stop codons affect 5' splice site selection by surveillance of splicing

Pre-mRNA splicing involves recognition of a consensus sequence at the 5' splice site (SS). However, only some of the many potential sites that conform to the consensus are true ones, whereas the majority remain silent and are not normally used for splicing. We noticed that in most cases the utilization of such a latent intronic 5' SS for splicing would introduce an in-frame stop codon into the resultant mRNA. This finding suggested a link between SS selection and maintenance of an ORF within the mRNA. Here we tested this idea by analyzing the splicing of pre-mRNAs in which in-frame stop codons upstream of a latent 5' SS were mutated. We found that splicing with the latent site is indeed activated by such mutations. Our findings predict the existence of a checking mechanism, as a component of the nuclear pre-mRNA splicing machine, to ensure the maintenance of an ORF. This notion is highly important for accurate gene expression, as perturbations that would lead to splicing at these latent sites are expected to introduce in-frame stop codons into the majority of mRNAs.

Reducing the flexibility of retinal restores a wild-type-like photocycle in bacteriorhodopsin mutants defective in protein-retinal coupling

The thermal re-isomerization of retinal from the 13-cis to the all-trans state is a key step in the final stages of the photocycle of the light-driven proton pump, bacteriorhodopsin. This step is greatly slowed upon replacement of Leu-93, a residue in van der Waals contact with retinal. The most likely role of this key interaction is that it restricts the flexibility of retinal. To test this hypothesis, we have exchanged native retinal in Leu-93 mutants with bridged retinal analogs that render retinal less flexible by restricting free rotation around either the C10-C11 (9,11-bridged retinal) or C12-C13 (11,13-bridged retinal) single bonds. The effect of the analogs on the photocycle was then determined spectroscopically by taking advantage of the previous finding that the decay of the O intermediate in the Leu-93 mutants provides a convenient marker for retinal re-isomerization. Time-resolved spectroscopic studies showed that both retinal analogs resulted in a dramatic acceleration of the photocycling time by increasing the rate of decay of the O intermediate. In particular, exchange of native retinal in the Leu-93 --> Ala mutant with the 9,11-bridged retinal resulted in an acceleration of the decay of the O intermediate to a rate similar to that seen in wild-type bacteriorhodopsin. We conclude that the protein-induced restriction of conformational flexibility in retinal is a key structural requirement for efficient protein-retinal coupling in the bacteriorhodopsin photocycle.