Point of Care Molecular Testing: Community-Based Rapid Next-Generation Sequencing to Support Cancer Care.

Purpose: Biomarker data are critical to the delivery of precision cancer care. The average turnaround of next-generation sequencing (NGS) reports is over 2 weeks, and in-house availability is typically limited to academic centers. Lengthy turnaround times for biomarkers can adversely affect outcomes. Traditional workflows involve moving specimens through multiple facilities. This study evaluates the feasibility of rapid comprehensive NGS using the Genexus integrated sequencer and a novel streamlined workflow in a community setting. Methods: A retrospective chart review was performed to assess the early experience and performance characteristics of a novel approach to biomarker testing at a large community center. This approach to NGS included an automated workflow utilizing the Genexus integrated sequencer, validated for clinical use. NGS testing was further integrated within a routine immunohistochemistry (IHC) service, utilizing histotechnologists to perform technical aspects of NGS, with results reported directly by anatomic pathologists. Results: Between October 2020 and October 2021, 578 solid tumor samples underwent genomic profiling. Median turnaround time for biomarker results was 3 business days (IQR: 2-5). Four hundred eighty-one (83%) of the cases were resulted in fewer than 5 business days, and 66 (11%) of the cases were resulted simultaneously with diagnosis. Tumor types included lung cancer (310), melanoma (97), and colorectal carcinoma (68), among others. NGS testing detected key driver alterations at expected prevalence rates: lung EGFR (16%), ALK (3%), RET (1%), melanoma BRAF (43%), colorectal RAS/RAF (67%), among others. Conclusion: This is the first study demonstrating clinical implementation of rapid NGS. This supports the feasibility of automated comprehensive NGS performed and interpreted in parallel with diagnostic histopathology and immunohistochemistry. This novel approach to biomarker testing offers considerable advantages to clinical cancer care.

A Guide to Implementing Immune Checkpoint Inhibitors within a Cancer Program: Experience from a Large Canadian Community Centre.

The increased use of immune checkpoint inhibitors across cancer programs has created the need for standardized patient assessment, education, monitoring, and management of immune-related adverse events (irAEs). At William Osler Health System in Brampton, Ontario, a practical step-wise approach detailing the implementation of cancer immunotherapy in routine practice was developed. The approach focuses on four key steps: (1) identification of patient educators; (2) development of patient education materials; (3) development of patient monitoring tools; (4) involvement and education of multidisciplinary teams. Here, we provide an in-depth description of what was included in each step and how we integrated the different elements of the program. For each step, resources, tools, and materials that may be useful for patients, healthcare providers, and multidisciplinary teams were developed or modified based on existing materials. At our centre, the program led to improved patient comprehension of irAEs, the ability to act on symptoms (patient self-efficacy), and low rates of emergency room visits at first presentation for irAEs. We recognize that centres may need to tailor the approaches to their institutional policies and encourage centres to adapt and modify the forms and tools according to their needs and requirements.

Pan-cancer analysis of longitudinal metastatic tumors reveals genomic alterations and immune landscape dynamics associated with pembrolizumab sensitivity.

Serial circulating tumor DNA (ctDNA) monitoring is emerging as a non-invasive strategy to predict and monitor immune checkpoint blockade (ICB) therapeutic efficacy across cancer types. Yet, limited data exist to show the relationship between ctDNA dynamics and tumor genome and immune microenvironment in patients receiving ICB. Here, we present an in-depth analysis of clinical, whole-exome, transcriptome, and ctDNA profiles of 73 patients with advanced solid tumors, across 30 cancer types, from a phase II basket clinical trial of pembrolizumab (NCT02644369) and report changes in genomic and immune landscapes (primary outcomes). Patients stratified by ctDNA and tumor burden dynamics correspond with survival and clinical benefit. High mutation burden, high expression of immune signatures, and mutations in BRCA2 are associated with pembrolizumab molecular sensitivity, while abundant copy-number alterations and B2M loss-of-heterozygosity corresponded with resistance. Upon treatment, induction of genes expressed by T cell, B cell, and myeloid cell populations are consistent with sensitivity and resistance. We identified the upregulated expression of PLA2G2D, an immune-regulating phospholipase, as a potential biomarker of adaptive resistance to ICB. Together, these findings provide insights into the diversity of immunogenomic mechanisms that underpin pembrolizumab outcomes.

Clinicopathologic factors that influence prognosis and survival outcomes in men with metastatic castration-resistant prostate cancer treated with Radium-223.

BACKGROUND: In men with metastatic castration-resistant prostate cancer (mCRPC) with primarily bone metastases, radium-223 (223 Ra) improves overall survival (OS). However, the selection of 223 Ra is not guided by specific validated clinicopathologic factors, and thus outcomes are heterogeneous. PATIENTS AND METHODS: This retrospective survival analysis was performed in men with mCRPC treated with 223 Ra at our cancer center. Demographics and disease characteristics were collected. OS was calculated using the Kaplan-Meier method (log-rank). The potential prognostic factors were determined using both univariable (UVA) and multivariable analysis (MVA) (Cox-regression) methods. RESULTS: In total, 150 patients with a median age of 74 years (52-93) received 223 Ra between May 2015 and July 2018, and 58% had 6-20 bone metastases. Ninety-four (63%) patients received >4 223 Ra doses, and 56 (37%) received ≤4. The following pre-treatment factors were analyzed (median [range]): eastern cooperative oncology group performance status (ECOG PS), (1 [0-3]); Albumin (ALB), (39 g/L [24-47]); alkaline phosphatase (ALP), (110 U/L [35-1633]); and prostate-specific antigen (PSA), (49 µg/L [0.83-7238]). The median OS for all patients was 14.5 months (95% CI: 11.2-18). These factors were associated with poor survival outcomes in UVA and MVA: ALB <35 g/L, ALP >150 U/L, ECOG PS 2-3, and PSA >80 µg/L. By assigning one point for each of these factors, a prognostic model was developed, wherein three distinct risk groups were identified: good, 0-1 (n = 103); intermediate, 2 (n = 30); and poor risk, 3-4 points (n = 17). The median OS was 19.4, 10.0, and 3.1 months, respectively (p < 0.001). CONCLUSIONS: Pre-treatment ALB, ALP, ECOG, and PSA, were significantly correlated with OS and could guide treatment selection for men with mCRPC by identifying those who are most or least likely to benefit from 223 Ra. Validation in an independent dataset is required prior to widespread clinical utilization.

Predicting Toxicity and Response to Pembrolizumab Through Germline Genomic HLA Class 1 Analysis.

Background: Human leukocyte antigen class 1 (HLA-1)-dependent immune activity is linked to autoimmune diseases. HLA-1-dependent CD8+ T cells are required for immune checkpoint blockade antitumor activity. It is unknown if HLA-1 genotype is predictive of toxicity to immune checkpoint blockade. Methods: Patients with advanced solid tumors stratified into 5 cohorts received single agent pembrolizumab (anti-programmed cell death-1) 200 mg intravenously every 3 weeks in an investigator-initiated phase II trial (Investigator-Initiated Phase II Study of Pembrolizumab Immunological Response Evaluation study, NCT02644369). Germline whole-exome sequencing of peripheral blood mononuclear cells was performed using the Illumina HiSeq2500 platform. HLA-1 haplotypes were predicted from whole-exome sequencing using HLAminer and HLAVBSeq. Heterozygosity of HLA-A, -B, and -C, individual HLA-1 alleles, and HLA haplotype dimorphism at positions -21 M and -21 T of the HLA-A and -B leader sequence were analyzed as predictors of toxicity defined as grade 2 or greater immune-related adverse events and clinical benefit defined as complete or partial response, or stable disease for 6 or more cycles of pembrolizumab. Statistical significance tests were 2-sided. Results: In the overall cohort of 101 patients, the frequency of toxicity and clinical benefit from pembrolizumab was 22.8% and 25.7%, respectively. There was no association between any of the HLA-1 loci or alleles with toxicity. HLA-C heterozygosity had an association with decreased clinical benefit relative to HLA-C homozygosity when controlling for cohort (odds ratio = 0.28, 95% confidence interval = 0.09 to 0.91, P = .04). HLA-A and -B haplotype -21 M/T dimorphism and heterozygosity of HLA-A, -B, and -C were not predictive of outcomes. Conclusions: HLA-C heterozygosity may predict decreased response to pembrolizumab. Prospective validation is required.

Systematic Review and STARD Scoring of Renal Cell Carcinoma Circulating Diagnostic Biomarker Manuscripts.

BACKGROUND: No validated molecular biomarkers exist to help guide diagnosis of renal cell carcinoma (RCC) patients. We seek to evaluate the quality of published RCC circulating diagnostic biomarker manuscripts using the Standards for Reporting of Diagnostic Accuracy Studies (STARD) guidelines. METHODS: The phrase "(renal cell carcinoma OR renal cancer OR kidney cancer OR kidney carcinoma) AND circulating AND (biomarkers OR cell free DNA OR tumor DNA OR methylated cell free DNA OR methylated tumor DNA)" was searched in Embase, MEDLINE, and PubMed in March 2018. Relevant manuscripts were scored using 41 STARD subcriteria for a maximal score of 26 points. All tests of statistical significance were 2 sided. RESULTS: The search identified 535 publications: 27 manuscripts of primary research were analyzed. The median STARD score was 11.5 (range = 7-16.75). All manuscripts had appropriate abstracts, introductions, and distribution of alternative diagnoses. None of the manuscripts stated how indeterminant data were handled or if adverse events occurred from performing the index test or reference standard. Statistically significantly higher STARD scores were present in manuscripts reporting receiver operator characteristic curves (P < .001), larger sample sizes (P = .007), and after release of the original STARD statement (P = .005). CONCLUSIONS: Most RCC circulating diagnostic biomarker manuscripts poorly adhere to the STARD guidelines. Future studies adhering to STARD guidelines may address this unmet need.

Real-World Assessment of Clinical Outcomes Among First-Line Sunitinib Patients with Clear Cell Metastatic Renal Cell Carcinoma (mRCC) by the International mRCC Database Consortium Risk Group.

BACKGROUND: International Metastatic Renal Cell Carcinoma (mRCC) Database Consortium (IMDC) risk groups are important when considering therapeutic options for first-line treatment. MATERIALS AND METHODS: Adult patients with clear cell mRCC initiating first-line sunitinib between 2010 and 2018 were included in this retrospective database study. Median time to treatment discontinuation (TTD) and overall survival (OS) were estimated using Kaplan-Meier analysis. Outcomes were stratified by IMDC risk groups and evaluated for those in the combined intermediate and poor risk group and separately for those in the intermediate risk group with one versus two risk factors. RESULTS: Among 1,769 patients treated with first-line sunitinib, 318 (18%) had favorable, 1,031 (58%) had intermediate, and 420 (24%) had poor IMDC risk. Across the three risk groups, patients had similar age, gender, and sunitinib initiation year. Median TTD was 15.0, 8.5, and 4.2 months in the favorable, intermediate, and poor risk groups, respectively, and 7.1 months in the combined intermediate and poor risk group. Median OS was 52.1, 31.5, and 9.8 months in the favorable, intermediate, and poor risk groups, respectively, and 23.2 months in the combined intermediate and poor risk group. Median OS (35.1 vs. 21.9 months) and TTD (10.3 vs. 6.6 months) were significantly different between intermediate risk patients with one versus two risk factors. CONCLUSION: This real-world study found a median OS of 52 months for patients with favorable IMDC risk treated with first-line sunitinib, setting a new benchmark on clinical outcomes of clear cell mRCC. Analysis of intermediate risk group by one or two risk factors demonstrated distinct clinical outcomes. IMPLICATIONS FOR PRACTICE: This analysis offers a contemporary benchmark for overall survival (median, 52.1 months; 95% confidence interval, 43.4-61.2) among patients with clear cell metastatic renal cell carcinoma who were treated with sunitinib as first-line therapy in a real-world setting and classified as favorable risk according to International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk group classification. This study demonstrates that clinical outcomes differ between IMDC risk groups as well as within the intermediate risk group based on the number of risk factors, thus warranting further consideration of risk group when counseling patients about therapeutic options and designing clinical trials.

Personalized circulating tumor DNA analysis as a predictive biomarker in solid tumor patients treated with pembrolizumab.

Immune checkpoint blockade (ICB) provides clinical benefit to a subset of patients with cancer. However, existing biomarkers do not reliably predict treatment response across diverse cancer types. Limited data exist to show how serial circulating tumor DNA (ctDNA) testing may perform as a predictive biomarker in patients receiving ICB. We conducted a prospective phase II clinical trial to assess ctDNA in five distinct cohorts of patients with advanced solid tumors treated with pembrolizumab (NCT02644369). We applied bespoke ctDNA assays to 316 serial plasma samples obtained at baseline and every three cycles from 94 patients. Baseline ctDNA concentration correlated with progression-free survival, overall survival, clinical response and clinical benefit. This association became stronger when considering ctDNA kinetics during treatment. All 12 patients with ctDNA clearance during treatment were alive with median 25 months follow up. This study demonstrates the potential for broad clinical utility of ctDNA-based surveillance in patients treated with ICB.

Systematic review and REMARK scoring of renal cell carcinoma prognostic circulating biomarker manuscripts.

BACKGROUND: No validated molecular biomarkers exist to help guide prognosis of renal cell carcinoma (RCC) patients. We seek to evaluate the quality of published prognostic circulating RCC biomarker manuscripts using the Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) guidelines. METHODS: The phrase "(renal cell carcinoma OR renal cancer OR kidney cancer OR kidney carcinoma) AND circulating AND (biomarkers OR cell free DNA OR tumor DNA OR methylated cell free DNA OR methylated tumor DNA)" was searched in Embase, Medline and PubMed March 2018. Relevant manuscripts were scored using 48 REMARK sub-criteria for a maximal score of 20 points. RESULTS: The search identified 535 publications: 33 were manuscripts of primary research and were analyzed. The mean REMARK score was 10.6 (range 6.42-14.2). All manuscripts stated their biomarker, study objectives and method of case selection. The lowest scoring criteria: time lapse between storage of blood/serum and marker assay (n = 2) and lack of flow diagram (n = 2). REMARK scores were significantly higher in publications stating adherence to REMARK guidelines (p = 0.0307) and reporting statistically significant results (p = 0.0318). CONCLUSIONS: Most RCC prognostic biomarker manuscripts poorly adhere to the REMARK guidelines. Better designed studies and appropriate reporting are required to address this urgent unmet need.

Serum PD-1 Is Elevated after Pembrolizumab Treatment but Has No Predictive Value.

Immune-checkpoint blockade (ICB) uses antibody targeting of specific inhibitory receptors and ligands. The major limitations of ICB, such as high cost, limited success rate, and immune-related adverse events (irAE), highlight the need for predictive biomarkers. We analyzed pre-immunotherapy and post-immunotherapy serum samples of 24 patients treated with pembrolizumab for changes in PD-1 and over 1,000 additional protein markers using a multiplex proximity extension assay (PEA) to identify potential predictive biomarkers of response and/or toxicity. Candidates were selected based on the criteria that at least 2 patients within any of 3 patient groups (responders without irAEs, responders with irAEs, or nonresponders with irAEs) had either a ≥4-fold increase or 4-fold decrease in expression post-immunotherapy. Female and male control samples were used as technical duplicates. A patient group with no response and no irAEs was used to exclude candidates. Following treatment with pembrolizumab, there was a relative increase of PD-1 in the serum of all patients, compared with controls (average 4.4-fold). We identified 7 additional serum proteins that met our candidate selection criteria. These candidate markers did not have any significant association with response or toxicity to pembrolizumab. Overall, we show that serum PD-1 increases post-therapy with pembrolizumab treatment but has no predictive value for response or toxicity in this small set of patients.

Rational design and identification of immuno-oncology drug combinations.

BACKGROUND: Clinical trials investigating immuno-oncology (IO) drug combinations are largely based on empiricism or limited non-clinical evaluations. This study identified the current combination IO drug clinical trials and investigated how tumour molecular profiling can help rationalise IO drug combinations. METHODS: IO targets were identified via PubMed search and expert opinion. IO drugs were compiled by searching the National Cancer Institute Drug Dictionary and pharmaceutical pipelines, August 2016. Combination IO trials were obtained by searching doublet IO drug combinations in www.clinicaltrials.gov from September to November 2016. IO target gene expressions were extracted from The Cancer Genome Atlas (TCGA) data set and compared with normal tissues from the Genotype-Tissue Expression database. Differentially expressed genes for each cancer were determined using the Wilcoxon rank-sum test, and p-values were corrected for multiple testing. RESULTS: In total, 178 IO targets were identified; 90 targets have either regulatory approved or investigational therapeutics. In total, 410 combination trials involving ≥2 IO drugs were identified: skin (n = 102) and genitourinary (n = 41) malignancies have the largest number of combination IO trials; 109 trials involved >2 disease sites. Summative patient accrual estimates among all trials are 71,345. Trials combining cytotoxic T lymphocyte antigen 4 (CTLA4) with programmed cell death protein 1 (n = 79) and CTLA4 with programmed cell death ligand 1 (n = 44) are the most common. Gene expression data from TCGA were mined to extract the 178 IO targets in 9089 tumours originating from 19 cancer types. IO target expression-clustered heatmap analysis identified several promising drug combinations. CONCLUSION: Our review highlights the great interest in combination IO clinical trials. Our analysis can enrich IO combination therapy selection.

Update on Programmed Death-1 and Programmed Death-Ligand 1 Inhibition in the Treatment of Advanced or Metastatic Non-Small Cell Lung Cancer.

PURPOSE: Non-small-cell lung cancer (NSCLC) has a large worldwide prevalence with a high mortality rate. Chemotherapy has offered modest improvements in survival over the past two decades. Immune checkpoint modulation with programmed death-1 (PD-1) or programmed death-ligand 1 (PD-L1) inhibition has shown the promise of changing the future landscape of cancer therapy. This update reviews recent advances in the treatment of NSCLC with immune checkpoint modulation. METHODS: Publications and proceedings were identified from searching PubMed and proceedings from the annual meetings of the American Society of Clinical Oncology, European Society for Medical Oncology, and European Lung Cancer Conference. RESULTS: Atezolizumab, nivolumab, and pembrolizumab increase overall survival in second-line treatment of Stage III/IV squamous and non-squamous NSCLC when compared to docetaxel. Pembrolizumab increases progression-free survival in the first-line treatment of Stage IV NSCLC with 50% PD-L1 expression when compared to platinum-based chemotherapy. Combination therapy with chemotherapy and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) inhibitors has shown promise in early trials. CONCLUSION: Immune checkpoint modulation produces durable responses and overall survival benefits with less toxicity compared to conventional chemotherapy. Future investigations are combining PD-1/L1 inhibition with chemotherapy, targeted therapy, or other immuno-oncology agents in an effort to further improve efficacy.

Transplantation of umbilical cord blood-derived cells for novel indications in regenerative therapy or immune modulation: a scoping review of clinical studies.

Although used mainly for transplantation of hematopoietic stem cells in the treatment of blood disorders, umbilical cord blood (UCB)-based therapies are now being used increasingly for novel applications in nonhematopoietic diseases and as a form of cellular regenerative therapy or immune modulation. We performed a systematic scoping review by searching Medline, EMBASE, and the Cochrane Library for published articles, and we searched www.clinicaltrials.com and the World Health Organization International Clinical Trials Registry Platform to describe the breadth of published studies and ongoing clinical activity in umbilical cord-based cellular therapy for regenerative therapy and immune modulation. The most commonly published area of expertise in the use of UCB-derived cellular transplantation for novel indications is for neurological disorders and this remains the most active area of study in ongoing registered trials. An increasingly broad range of disorders, however, are reflected in ongoing registered trials, which suggests greater activity, interest, and investment in UCB-derived cellular therapy. Interestingly, adult patients compose the majority of patients reported in published reports and registered ongoing clinical studies continue to enroll predominantly adult subjects. Geographically, Asian countries appear most active in UCB-derived cellular therapy and our analysis of ongoing studies suggests this trend will likely continue. Regular assessment of published and ongoing activity in UCB transplantation for emerging novel indications will be critical for informing UCB banking establishments and funding agencies to guide changes in banking practices related to emerging trends in cell therapy.

Increasing the efficiency of bacterial transcription simulations: when to exclude the genome without loss of accuracy.

BACKGROUND: Simulating the major molecular events inside an Escherichia coli cell can lead to a very large number of reactions that compose its overall behaviour. Not only should the model be accurate, but it is imperative for the experimenter to create an efficient model to obtain the results in a timely fashion. Here, we show that for many parameter regimes, the effect of the host cell genome on the transcription of a gene from a plasmid-borne promoter is negligible, allowing one to simulate the system more efficiently by removing the computational load associated with representing the presence of the rest of the genome. The key parameter is the on-rate of RNAP binding to the promoter (k_on), and we compare the total number of transcripts produced from a plasmid vector generated as a function of this rate constant, for two versions of our gene expression model, one incorporating the host cell genome and one excluding it. By sweeping parameters, we identify the k_on range for which the difference between the genome and no-genome models drops below 5%, over a wide range of doubling times, mRNA degradation rates, plasmid copy numbers, and gene lengths. RESULTS: We assess the effect of the simulating the presence of the genome over a four-dimensional parameter space, considering: 24 min

Dark proteins: effect of inclusion body formation on quantification of protein expression.

Plasmid-borne gene expression systems have found wide application in the emerging fields of systems biology and synthetic biology, where plasmids are used to implement simple network architectures, either to test systems biology hypotheses about issues such as gene expression noise or as a means of exerting artificial control over a cell's dynamics. In both these cases, fluorescent proteins are commonly applied as a means of monitoring the expression of genes in the living cell, and efforts have been made to quantify protein expression levels through fluorescence intensity calibration and by monitoring the partitioning of proteins among the two daughter cells after division; such quantification is important in formulating the predictive models desired in systems and synthetic biology research. A potential pitfall of using plasmid-based gene expression systems is that the high protein levels associated with expression from plasmids can lead to the formation of inclusion bodies, insoluble aggregates of misfolded, nonfunctional proteins that will not generate fluorescence output; proteins caught in these inclusion bodies are thus "dark" to fluorescence-based detection methods. If significant numbers of proteins are incorporated into inclusion bodies rather than becoming biologically active, quantitative results obtained by fluorescent measurements will be skewed; we investigate this phenomenon here. We have created two plasmid constructs with differing average copy numbers, both incorporating an unregulated promoter (P(LtetO-1) in the absence of TetR) expressing the GFP derivative enhanced green fluorescent protein (EGFP), and inserted them into Escherichia coli bacterial cells (a common model organism for work on the dynamics of prokaryotic gene expression). We extracted the inclusion bodies, denatured them, and refolded them to render them active, obtaining a measurement of the average number of EGFP per cell locked into these aggregates; at the same time, we used calibrated fluorescent intensity measurements to determine the average number of active EGFP present per cell. Both measurements were carried out as a function of cellular doubling time, over a range of 45-75 min. We found that the ratio of inclusion body EGFP to active EGFP varied strongly as a function of the cellular growth rate, and that the number of "dark" proteins in the aggregates could in fact be substantial, reaching ratios as high as approximately five proteins locked into inclusion bodies for every active protein (at the fastest growth rate), and dropping to ratios well below 1 (for the slowest growth rate). Our results suggest that efforts to compare computational models to protein numbers derived from fluorescence measurements should take inclusion body loss into account, especially when working with rapidly growing cells.

Simplification of stochastic chemical reaction models with fast and slow dynamics.

Biological systems often involve chemical reactions occurring in low-molecule-number regimes, where fluctuations are not negligible and thus stochastic models are required to capture the system behaviour. The resulting models are generally quite large and complex, involving many reactions and species. For clarity and computational tractability, it is important to be able to simplify these systems to equivalent ones involving fewer elements. While many model simplification approaches have been developed for deterministic systems, there has been limited work on applying these approaches to stochastic modelling. Here, we describe a method that reduces the complexity of stochastic biochemical network models, and apply this method to the reduction of a mammalian signalling cascade and a detailed model of the process of bacterial gene expression. Our results indicate that the simplified model gives an accurate representation for not only the average numbers of all species, but also for the associated fluctuations and statistical parameters.

Extracting biochemical parameters for cellular modeling: A mean-field approach.

Recent developments in molecular biology have made it feasible to carry out experimental verification of mathematical models for biochemical processes, offering the eventual prospect of creating a detailed, validated picture of gene expression. A persistent difficulty with this long-term goal is the incompleteness of the kinetic information available in the literature: Many rate constants cannot or have not yet been measured. Here, we present a method of filling in missing parameters using an approach conceptually analogous to mean-field approaches in statistical mechanics: When studying a particular gene, we extract key parameters by considering the averaged effect of all other genes in the system, analogously to considering the averaged magnetic field in a physical spin model. This methodology has been applied to account for the effect of the presence of the Escherichia coli genome on the availability of key enzymes involved in gene expression (RNA polymerases and ribosomes), yielding the number of free enzymes as a function of cellular growth rate. These conclusions have been obtained by deriving genome-wide averages and matching them to bulk literature values of E. coli K-12 and B/r. Average rate constants have been found for RNA polymerases and ribosomes binding to promoter and ribosome-binding sites, respectively; these results suggest that cells vary not only their production rates of RNA polymerase and ribosomes under different growth-rate conditions but also change their global level of transcriptional/translational activation and repression, thus altering the average binding rate constants for these enzymes. To test the mean-field method, the results from the genome-wide averages have been applied to the induced lac operon, where our derived on-rate for binding of RNA polymerase to the promoter is in good agreement with previous experimental results.