Feasibility of delivering supervised exercise training following surgical resection and during adjuvant chemotherapy for pancreatic ductal adenocarcinoma (PRECISE): a case series

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive neoplasm, with surgical resection and adjuvant chemotherapy the only curative treatment. Treatment-related toxicities place a considerable burden on patients although exercise training has shown promise is helping to manage such adversities and facilitate rehabilitation. The feasibility and safety of exercise training as a supportive therapy during adjuvant chemotherapy remains unknown.

METHODS

Patients with PDAC were screened post-surgical resection and enrolled in a 16-week, progressive, concurrent exercise programme alongside their chemotherapy regimen. Feasibility was the primary objective detailing recruitment, retention and adherence rates throughout as well as the safety and fidelity of the intervention. Secondarily, the impact on functional fitness and patient-reported outcomes was captured at baseline, post-intervention and 3-month follow up.

RESULTS

Eight patients consented to participate in this trial, with five proceeding to enrol in exercise training. Concurrent exercise training is feasible and safe during adjuvant chemotherapy and prevented an expected decline in functional fitness and patient-reported outcomes during this time.

DISCUSSION

This case series provides preliminary evidence that concurrent exercise training during adjuvant therapy is safe, feasible and well tolerated, preventing an expected decline in functional fitness, muscular strength and health-related quality of life (HRQoL). Given the adverse effects of treatment, these findings are promising and provide further evidence for the inclusion of exercise training as a standard of care for surgical rehabilitation and managing treatment-related toxicities. Future research should explore the impact of exercise training during neoadjuvant chemotherapy, with prehabilitation now standard practice for borderline resectable disease.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04305067, prospectively registered 12/03/2020, https://classic.

CLINICALTRIALS

gov/ct2/show/NCT04305067 .

OGC O02 The prognostic effect of pathological lymph node regression after neoadjuvant chemotherapy for oesophageal adenocarcinoma – a multicentre study

Background

The prognostic benefits of primary tumour and lymph node (LN) downstaging after neoadjuvant chemotherapy for oesophageal adenocarcinoma are well described. Pathological primary tumour regression grading (TRG) is widely used in the assessment of response to chemotherapy and has been shown to have prognostic value in this patient group. However, there is a lack of robust evidence regarding the prognostic effect of pathological response in LN despite emerging evidence of a discrepancy, up to 25% of patients in some studies, between TRG in the primary tumour and response in regional LNs. Although primary tumour regression is routinely documented as part of the standard pathological reporting of oesophagectomy specimens, LN regression is generally overlooked despite it's potential prognostic value. The aim of this study was to investigate the relationship between pathological response in LN, tumour recurrence and survival.

Methods

Multicentre cohort study including 763 patients with oesophageal adenocarcinoma treated with neoadjuvant chemotherapy followed by surgery at Guy's and St Thomas’ NHS Foundation Trust (NHS-FT), The Royal Marsden NHS-FT, University Hospitals Birmingham NHS-FT, University Hospital Southampton NHS-FT and Belfast Health and Social Care Trust. Tumour regression was assessed in the primary tumour (as described by Mandard) and, retrospectively, in LNs retrieved from oesophagectomy specimens. LN were graded according to the proportion of fibrosis and residual tumour providing a LN regression score (LNRS). LNRS 1, complete response; LNRS 2, < 10% remaining tumour; LNRS 3, 10–50% remaining tumour; LNRS 4, > 50% viable tumour; LNRS 5, no evidence of response. Regression was defined as a LNRS of 1–3. Patients were classified as LN negative (no evidence of tumour or regression in any LN), complete LN-responders (evidence of regression ≥1 LN, no residual tumour in any LN), partial LN-responders (evidence of regression ≥1 LN with residual tumour ≥1 LN) and LN non-responders (no or minimal regression in any LN). Survival analysis was performed using multivariable Cox regression providing hazard ratios (HR) with 95% confidence intervals (CI) adjusting for age, gender, chemotherapy regimen, clinical stage, tumour grade, lympho-vascular invasion and primary tumour response.

Results

Mean age was 63 years with the majority male (86.2%). In total, 17,930 LN from 763 patients were analysed for evidence of response to chemotherapy. Overall, 243 (31.8%) patients were classified as LN negative, 62 (8.1%) as complete LN-responders, 155 (20.3%) as partial LN-responders and 303 (39.7%) as LN non-responders. Less than half (322/763, 42.2%) of patients demonstrated a pathological response in the primary tumour (Mandard score 1–3). Some patients had a LN response in the absence of a response in the primary tumour (97/431, 22.5%). Multivariable Cox regression survival analysis demonstrated improved overall survival in complete LN-responders (HR 0.37 95% CI 0.24–0.58), partial LN-responders (HR 0.70 95% CI 0.55–0.89) and LN negative patients (HR 0.34 95% CI 0.26–0.44) compared to LN non-responders. Similar results were observed for disease-free survival (complete LN-responders, HR 0.34 95% CI 0.22–0.53; partial LN-responders, HR 0.74 95% CI 0.58–0.93; LN negative, HR 0.33 95% CI 0.25–0.42). Rates of tumour recurrence were lower in patients who demonstrated a LN response or had negative LN (LN negative 23.0% vs complete LN-responders 19.4% vs partial LN-responders 50.3% vs LN non-responders 66.7%, p<0.001).

Conclusions

In this cohort of patients with oeosphageal adenocarcinoma treated with neoadjuvant chemotherapy prior to surgical resection, LN regression was a strong predictive factor for better survival. This relationship was independent of primary tumour response, which was discordant in a significant number of patients. Complete LN-responders had equivalent survival to those with negative LN. Complete and partial LN-responders had better survival than LN non-responders. Evaluation and documentation of LN regression should be considered during the standard pathological reporting of oesophagectomy specimens.

Design and synthesis of multifunctional microtubule targeting agents endowed with dual pro-apoptotic and anti-autophagic efficacy

Autophagy is a lysosome dependent cell survival mechanism and is central to the maintenance of organismal homeostasis in both physiological and pathological situations. Targeting autophagy in cancer therapy attracted considerable attention in the past as stress-induced autophagy has been demonstrated to contribute to both drug resistance and malignant progression and recently interest in this area has re-emerged. Unlocking the therapeutic potential of autophagy modulation could be a valuable strategy for designing innovative tools for cancer treatment. Microtubule-targeting agents (MTAs) are some of the most successful anti-cancer drugs used in the clinic to date. Scaling up our efforts to develop new anti-cancer agents, we rationally designed multifunctional agents 5a-l with improved potency and safety that combine tubulin depolymerising efficacy with autophagic flux inhibitory activity. Through a combination of computational, biological, biochemical, pharmacokinetic-safety, metabolic studies and SAR analyses we identified the hits 5i,k. These MTAs were characterised as potent pro-apoptotic agents and also demonstrated autophagy inhibition efficacy. To measure their efficacy at inhibiting autophagy, we investigated their effects on basal and starvation-mediated autophagic flux by quantifying the expression of LC3II/LC3I and p62 proteins in oral squamous cell carcinoma and human leukaemia through western blotting and by immunofluorescence study of LC3 and LAMP1 in a cervical carcinoma cell line. Analogues 5i and 5k, endowed with pro-apoptotic activity on a range of hematological cancer cells (including ex-vivo chronic lymphocytic leukaemia (CLL) cells) and several solid tumor cell lines, also behaved as late-stage autophagy inhibitors by impairing autophagosome-lysosome fusion.

P-OGC95 Understanding the molecular age of Barrett’s oesophagus in a population-representative sample of patients

Background

The incidence of oesophageal adenocarcinoma (OAC) increases dramatically with patient age but only a small proportion of patients with diagnosed Barrett’s oesophagus (BO), the precursor to OAC, will develop dysplasia and/or cancer. Beyond chronological age, biomarkers of progression that capture biological aging offer largely untapped potential for objectively identifying BO patients at highest risk of progression, who could undergo personalised surveillance at shorter intervals. We have developed computational tools to determine tissue-specific aging using genome-wide methylation data as a “molecular clock” for estimating patient-specific BO dwell times at the time of incident diagnosis that cannot be clinically measured by other means. 

Methods

Using the population-based Northern Ireland BO register in a retrospective study, we have identified 46 non-dysplastic BO patients who have 2-4 serial endoscopic biopsies each, and have not progressed to OAC (age range 29-77 years).  FFPE biopsies for 10 age-matched patients who had prevalent HGD/OAC at index BO diagnosis were also retrieved. DNA has been extracted, quantified using fluorescence, quality checked through qPCR, and prepared for Illumina EPIC methylation arrays. We created a Python package called “MethylDrift” to determine genome-wide aging rates in patient data. Model outputs are used in the molecular clock for BO tissue age.

Results

We used MethylDrift to quantify aging rates in both cross-sectional data (population-level epigenetic drift) and longitudinal data within the same patients to obtain individual aging rates. Computational analyses using our previously developed Bayesian framework for the BO molecular clock will be applied to estimate the molecular age of BO in patients, i.e., how long the patient has been living with BO since onset of metaplasia. Results will be compared between age groups, birth cohorts, sex, and importantly between dysplastic and non-dysplastic BO to evaluate biomarker potential. Data analysis is ongoing, and the final results will be presented at the meeting.

Conclusions

Our results from this nested case-control study demonstrate feasibility and generate pilot data on molecular age as a proxy of BO duration at the time of incident diagnosis, in a large population-based registry of patients with BO. This will inform our computational tools for determining biological aging and can be applied in future work to investigate progression risk according to molecular age. Ultimately, this biomarker could inform surveillance frequency for BO patients, enable earlier detection of neoplastic progression, leading to improved patient outcomes and optimal distribution of limited endoscopy capacity for surveillance.

P-OGC08 Translational Insights from the Dual ErbB Inhibition in Oesophago-gastric Cancer (DEBIOC) Clinical Trial - A Bioinformatic Analysis

Background

Oesophageal Adenocarcinoma (OAC) incidence in the Western-world has increased markedly over 30 years. 5-year survival rates for patients remains below 20% with dismal response to neo-adjuvant or perioperative chemotherapy for operable tumours. The Dual ErbB Inhibition in Oesophago-gastric Cancer (DEBIOC) clinical trial assessed efficacy of combined oxaliplatin and capecitabine (Xelox) with dual ErbB inhibitor AZD8931 in providing additional benefit to operable patients compared to Xelox alone. We utilised a bioinformatic approach combing Almac Clara-T Transcriptional Discovery software with unsupervised machine learning methods to unveil translational clinical potential and biological insights from DEBIOC patient biopsy and resection specimens.

Methods

Using microarrays of DEBIOC patient specimens with documented clinical observations, we combined unsupervised machine learning techniques with state-of-the-art Almac Clara-T software to assess transcriptional changes between treatment types regarding the 10 hallmarks of cancer, characterised by representative gene-expression signatures and scores. These methods were employed to identify possible mechanisms of treatment resistance, evaluate changes in the tumour-microenvironment and determine clinically significant molecular subgroups in OAC. Differential expression and pathway analytics were used to describe signalling dissimilarities between clusters from unsupervised analysis and phenotypes respective to hallmarks of cancer, with alignment of sensitivities to single-gene drug targets for subgroups of interest.

Results

Unsupervised clustering analysis of biopsy specimens, resulted in the identification of two robust subgroups pre-treatment in OAC, determined to be significantly associated with the prediction of Mandard Score (Tumour Regression Grade 1-5) post-treatment (fishers exact p < 0.05). Differential expression analysis revealed distinguishing biology between subtypes and noted increased ErbB signalling in non-responding patients in addition to increased PI3K signalling, highlighting a potential mechanism of resistance to dual ErbB inhibition (nominal p-value <0.05, FDR p-value <0.2). Semi-supervised clustering revealed hallmark-specific-phenotypes associated with clinical observations including lymph node involvement, EGFR FISH classification, vascular invasion and progression events at BH adjusted p-values <0.05.

Conclusions

Our analysis has revealed translational insights into possible mechanisms of drug resistance as well as cancer hallmark-specific phenotypes significantly associated with clinico-pathological factors during the DEBIOC clinical trial. Continued analysis into resulting phenotypes and clusters combined with the alignment of single gene drug target sensitivities is anticipated to reveal novel molecular pathways driving phenotypic differences in an effort to further inform biological understanding and improve treatment response and survival outcomes in OAC patients. 

Machine learning to predict early recurrence after oesophageal cancer surgery

BACKGROUND

Early cancer recurrence after oesophagectomy is a common problem, with an incidence of 20-30 per cent despite the widespread use of neoadjuvant treatment. Quantification of this risk is difficult and existing models perform poorly. This study aimed to develop a predictive model for early recurrence after surgery for oesophageal adenocarcinoma using a large multinational cohort and machine learning approaches.

METHODS

Consecutive patients who underwent oesophagectomy for adenocarcinoma and had neoadjuvant treatment in one Dutch and six UK oesophagogastric units were analysed. Using clinical characteristics and postoperative histopathology, models were generated using elastic net regression (ELR) and the machine learning methods random forest (RF) and extreme gradient boosting (XGB). Finally, a combined (ensemble) model of these was generated. The relative importance of factors to outcome was calculated as a percentage contribution to the model.

RESULTS

A total of 812 patients were included. The recurrence rate at less than 1 year was 29·1 per cent. All of the models demonstrated good discrimination. Internally validated areas under the receiver operating characteristic (ROC) curve (AUCs) were similar, with the ensemble model performing best (AUC 0·791 for ELR, 0·801 for RF, 0·804 for XGB, 0·805 for ensemble). Performance was similar when internal-external validation was used (validation across sites, AUC 0·804 for ensemble). In the final model, the most important variables were number of positive lymph nodes (25·7 per cent) and lymphovascular invasion (16·9 per cent).

CONCLUSION

The model derived using machine learning approaches and an international data set provided excellent performance in quantifying the risk of early recurrence after surgery, and will be useful in prognostication for clinicians and patients.

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.

Transcriptomic profiling reveals three molecular phenotypes of adenocarcinoma at the gastroesophageal junction

Cancers occurring at the gastroesophageal junction (GEJ) are classified as predominantly esophageal or gastric, which is often difficult to decipher. We hypothesized that the transcriptomic profile might reveal molecular subgroups which could help to define the tumor origin and behavior beyond anatomical location. The gene expression profiles of 107 treatment-naïve, intestinal type, gastroesophageal adenocarcinomas were assessed by the Illumina-HTv4.0 beadchip. Differential gene expression (limma), unsupervised subgroup assignment (mclust) and pathway analysis (gage) were undertaken in R statistical computing and results were related to demographic and clinical parameters. Unsupervised assignment of the gene expression profiles revealed three distinct molecular subgroups, which were not associated with anatomical location, tumor stage or grade (p > 0.05). Group 1 was enriched for pathways involved in cell turnover, Group 2 was enriched for metabolic processes and Group 3 for immune-response pathways. Patients in group 1 showed the worst overall survival (p = 0.019). Key genes for the three subtypes were confirmed by immunohistochemistry. The newly defined intrinsic subtypes were analyzed in four independent datasets of gastric and esophageal adenocarcinomas with transcriptomic data available (RNAseq data: OCCAMS cohort, n = 158; gene expression arrays: Belfast, n = 63; Singapore, n = 191; Asian Cancer Research Group, n = 300). The subgroups were represented in the independent cohorts and pooled analysis confirmed the prognostic effect of the new subtypes. In conclusion, adenocarcinomas at the GEJ comprise three distinct molecular phenotypes which do not reflect anatomical location but rather inform our understanding of the key pathways expressed.

Multicentre cohort study to define and validate pathological assessment of response to neoadjuvant therapy in oesophagogastric adenocarcinoma

BACKGROUND

This multicentre cohort study sought to define a robust pathological indicator of clinically meaningful response to neoadjuvant chemotherapy in oesophageal adenocarcinoma.

METHODS

A questionnaire was distributed to 11 UK upper gastrointestinal cancer centres to determine the use of assessment of response to neoadjuvant chemotherapy. Records of consecutive patients undergoing oesophagogastric resection at seven centres between January 2000 and December 2013 were reviewed. Pathological response to neoadjuvant chemotherapy was assessed using the Mandard Tumour Regression Grade (TRG) and lymph node downstaging.

RESULTS

TRG (8 of 11 centres) was the most widely used system to assess response to neoadjuvant chemotherapy, but there was discordance on how it was used in practice. Of 1392 patients, 1293 had TRG assessment; data were available for clinical and pathological nodal status (cN and pN) in 981 patients, and TRG, cN and pN in 885. There was a significant difference in survival between responders (TRG 1-2; median overall survival (OS) not reached) and non-responders (TRG 3-5; median OS 2·22 (95 per cent c.i. 1·94 to 2·51) years; P < 0·001); the hazard ratio was 2·46 (95 per cent c.i. 1·22 to 4·95; P = 0·012). Among local non-responders, the presence of lymph node downstaging was associated with significantly improved OS compared with that of patients without lymph node downstaging (median OS not reached versus 1·92 (1·68 to 2·16) years; P < 0·001).

CONCLUSION

A clinically meaningful local response to neoadjuvant chemotherapy was restricted to the small minority of patients (14·8 per cent) with TRG 1-2. Among local non-responders, a subset of patients (21·3 per cent) derived benefit from neoadjuvant chemotherapy by lymph node downstaging and their survival mirrored that of local responders.

Molecular profiling of signet ring cell colorectal cancer provides a strong rationale for genomic targeted and immune checkpoint inhibitor therapies

BACKGROUND

Signet ring cell colorectal cancer (SRCCa) has a bleak prognosis. Employing molecular pathology techniques we investigated the potential of precision medicine in this disease.

METHODS

Using test (n=26) and validation (n=18) cohorts, analysis of mutations, DNA methylation and transcriptome was carried out. Microsatellite instability (MSI) status was established and immunohistochemistry (IHC) was used to test for adaptive immunity (CD3) and the immune checkpoint PDL1.

RESULTS

DNA methylation data split the cohorts into hypermethylated (n=18, 41%) and hypomethylated groups (n=26, 59%). The hypermethylated group predominant in the proximal colon was enriched for CpG island methylator phenotype (CIMP), BRAF V600E mutation and MSI (P<0.001). These cases also had a high CD3+ immune infiltrate (P<0.001) and expressed PDL1 (P=0.03 in intra-tumoural lymphoid cells). The hypomethylated group predominant in the distal colon did not show any characteristic molecular features. We also detected a common targetable KIT mutation (c.1621A>C) across both groups. No statistically significant difference in outcome was observed between the two groups.

CONCLUSIONS

Our data show that SRCCa phenotype comprises two distinct genotypes. The MSI+/CIMP+/BRAF V600E+/CD3+/PDL1+ hypermethylated genotype is an ideal candidate for immune checkpoint inhibitor therapy. In addition, one fourth of SRCCa cases can potentially be targeted by KIT inhibitors.

Comprehensive molecular pathology analysis of small bowel adenocarcinoma reveals novel targets with potential for clinical utility

Small bowel accounts for only 0.5% of cancer cases in the US but incidence rates have been rising at 2.4% per year over the past decade. One-third of these are adenocarcinomas but little is known about their molecular pathology and no molecular markers are available for clinical use.

Using a retrospective 28 patient matched normal-tumor cohort, next-generation sequencing, gene expression arrays and CpG methylation arrays were used for molecular profiling.

Next-generation sequencing identified novel mutations in IDH1, CDH1, KIT, FGFR2, FLT3, NPM1, PTEN, MET, AKT1, RET, NOTCH1 and ERBB4. Array data revealed 17% of CpGs and 5% of RNA transcripts assayed to be differentially methylated and expressed respectively (p < 0.01). Merging gene expression and DNA methylation data revealed CHN2 as consistently hypermethylated and downregulated in this disease (Spearman −0.71, p < 0.001). Mutations in TP53 which were found in more than half of the cohort (15/28) and Kazald1 hypomethylation were both were indicative of poor survival (p = 0.03, HR = 3.2 and p = 0.01, HR = 4.9 respectively).

By integrating high-throughput mutational, gene expression and DNA methylation data, this study reveals for the first time the distinct molecular profile of small bowel adenocarcinoma and highlights potential clinically exploitable markers.

Identification of galanin and its receptor GalR1 as novel determinants of resistance to chemotherapy and potential biomarkers in colorectal cancer

PURPOSE

A major factor limiting the effective clinical management of colorectal cancer (CRC) is resistance to chemotherapy. Therefore, the identification of novel, therapeutically targetable mediators of resistance is vital.

EXPERIMENTAL DESIGN

We used a CRC disease-focused microarray platform to transcriptionally profile chemotherapy-responsive and nonresponsive pretreatment metastatic CRC liver biopsies and in vitro samples, both sensitive and resistant to clinically relevant chemotherapeutic drugs (5-FU and oxaliplatin). Pathway and gene set enrichment analyses identified candidate genes within key pathways mediating drug resistance. Functional RNAi screening identified regulators of drug resistance.

RESULTS

Mitogen-activated protein kinase signaling, focal adhesion, cell cycle, insulin signaling, and apoptosis were identified as key pathways involved in mediating drug resistance. The G-protein-coupled receptor galanin receptor 1 (GalR1) was identified as a novel regulator of drug resistance. Notably, silencing either GalR1 or its ligand galanin induced apoptosis in drug-sensitive and resistant cell lines and synergistically enhanced the effects of chemotherapy. Mechanistically, GalR1/galanin silencing resulted in downregulation of the endogenous caspase-8 inhibitor FLIP(L), resulting in induction of caspase-8-dependent apoptosis. Galanin mRNA was found to be overexpressed in colorectal tumors, and importantly, high galanin expression correlated with poor disease-free survival of patients with early-stage CRC.

CONCLUSION

This study shows the power of systems biology approaches to identify key pathways and genes that are functionally involved in mediating chemotherapy resistance. Moreover, we have identified a novel role for the GalR1/galanin receptor-ligand axis in chemoresistance, providing evidence to support its further evaluation as a potential therapeutic target and biomarker in CRC.

Impact of Food and Predation on the Snowshoe Hare Cycle

Snowshoe hare populations in the boreal forests of North America go through 10-year cycles. Supplemental food and mammalian predator abundance were manipulated in a factorial design on 1-square-kilometer areas for 8 years in the Yukon. Two blocks of forest were fertilized to test for nutrient effects. Predator exclosure doubled and food addition tripled hare density during the cyclic peak and decline. Predator exclosure combined with food addition increased density 11-fold. Added nutrients increased plant growth but not hare density. Food and predation together had a more than additive effect, which suggests that a three-trophic-level interaction generates hare cycles.

Specificity of association between Bacillus isolates and genotypes of Lolium perenne and Trifolium repens from a grass – legume pasture

Specificity between plants and associated rhizosphere bacteria was investigated using species and genotypic mixtures of Lolium perenne L. (perennial ryegrass) and Trifolium repens L. (white clover) inoculated with Bacillus strains isolated from rhizosphere soil of the pasture plants. The genotypic identity of plants was controlled by using stolon tips (Trifolium) and tillers (Lolium) of three genotypes of each species collected from a 45-year-old permanent pasture. Inoculation of plants in the greenhouse with Bacillus isolates that had coexisted in the field with the Lolium component of a Lolium–Trifolium mixture increased Lolium root and shoot weight. Root and nodule weight of Trifolium in mixture regardless of its genotype was also higher when coexistent Bacillus–Lolium combinations were present. The presence of other coexistent Bacillus–plant or plant–plant combinations did not enhance performance of either pasture species. The identity of the Rhizobium leguminosarum biovar trifolii strains that formed Trifolium root nodules was unaffected by inoculation with Bacillus. Key words: Trifolium repens, Lolium perenne, Bacillus, specificity, rhizosphere, yield.

The influence of Rhizobium leguminosarum biovar. trifolii on the growth and neighbour relationships of Trifolium repens and three grasses

Trifolium repens was sampled from 10 areas dominated by each of Dactylis glomerata, Holcus lanatus, and Lolium perenne in each of three different-aged pastures. Cell extracts of nodule isolates of Rhizobium leguminosarum biovar. trifolii were compared using polyacrylamide gel electrophoresis. Each pasture contained a range of Rhizobium strains as defined by the protein profiles. No single strain was common to Trifolium sampled from the same grass species neighbourhood. The diversity of Rhizobium strains encountered was negatively correlated (r = −0.67; n = 9) with pasture age; old pastures showed a decrease in strain diversity. In addition, in the oldest pasture (45-year-old), tillers of the associated grasses were also sampled. In a glasshouse, ramets from each Trifolium clone and each of the three grass species were grown in all possible combinations with each of the three Rhizobium strains, plus Trifolium monocultures and an uninoculated control. All Trifolium clones gave increased yield in mixture with Lolium compared with yields with Dactylis and Holcus. Trifolium from the Holcus patches, in most cases, had higher yield than Trifolium from other grass patches. Rhizobium inoculation did not consistently increase Trifolium yield; it actually caused a decrease in yield when in mixture with Lolium. A significant Rhizobium × Trifolium interaction indicated a variable performance of each Trifolium genotype with different Rhizobium strains. The identity of the Trifolium clone had a significant effect on the yield of Holcus and Lolium, but not Dactylis. Total mixture yields were highest when Trifolium from a Lolium patch was part of the mixture. These results are discussed in the context of the hypothesis that Trifolium–grass coexistence is significantly influenced by Rhizobium strain differences.